Representativeness of Patients Enrolled in the Lung Cancer Master Protocol (Lung-MAP).

PURPOSE: Lung Cancer Master Protocol (Lung-MAP), a public-private partnership, established infrastructure for conducting a biomarker-driven master protocol in molecularly targeted therapies. We compared characteristics of patients enrolled in Lung-MAP with those of patients in advanced non-small-cell lung cancer (NSCLC) trials to examine if master protocols improve trial access. METHODS: We examined patients enrolled in Lung-MAP (2014-2020) according to sociodemographic characteristics. Proportions for characteristics were compared with those for a set of advanced NSCLC trials (2001-2020) and the US advanced NSCLC population using SEER registry data (2014-2018). Characteristics of patients enrolled in Lung-MAP treatment substudies were examined in subgroup analysis. Two-sided tests of proportions at an alpha of .01 were used for all comparisons. RESULTS: A total of 3,556 patients enrolled in Lung-MAP were compared with 2,215 patients enrolled in other NSCLC studies. Patients enrolled in Lung-MAP were more likely to be 65 years and older (57.2% v 46.3%; P < .0001), from rural areas (17.3% v 14.4%; P = .004), and from socioeconomically deprived neighborhoods (42.2% v 36.7%, P < .0001), but less likely to be female (38.6% v 47.2%; P < .0001), Asian (2.8% v 5.1%; P < .0001), or Hispanic (2.4% v 3.8%; P = .003). Among patients younger than 65 years, Lung-MAP enrolled more patients using Medicaid/no insurance (27.6% v 17.8%; P < .0001). Compared with the US advanced NSCLC population, Lung-MAP under represented patients 65 years and older (57.2% v 69.8%; P < .0001), females (38.6% v 46.0%; P < .0001), and racial or ethnic minorities (14.8% v 21.5%; P < .0001). CONCLUSION: Master protocols may improve access to trials using novel therapeutics for older patients and socioeconomically vulnerable patients compared with conventional trials, but specific patient exclusion criteria influenced demographic composition. Further research examining participation barriers for under represented racial or ethnic minorities in precision medicine clinical trials is warranted.

The New NCI Precision Medicine Trials.

Basket, umbrella, and platform trial designs (master protocols) have emerged over the last decade to study precision medicine approaches in oncology. First-generation trials like NCI-MATCH (Molecular Analysis for Therapy Choice) have proven the principle that studying targeted therapies on a large scale is feasible both from the laboratory and clinical perspectives. However, single-agent targeted therapies have shown limited ability to control metastatic disease, despite careful matching of drug to target. As such, newer approaches employing combinations of targeted therapy, or targeted therapy with standard therapies, need to be considered. The NCI has recently embarked on three second-generation precision medicine trials to address this need: ComboMATCH, iMATCH, and myeloMATCH. The design of these trials and necessary infrastructure are discussed in the following perspective.

Subclonal TP53 mutations are frequent and predict resistance to radioimmunotherapy in follicular lymphoma.

Although TP53 is commonly mutated in transformed follicular lymphoma, mutations are reported in <5% of pretreatment follicular lymphoma (FL) specimens. We assayed archival follicular B-cell non-Hodgkin lymphoma specimens from a completed clinical trial, Southwest Oncology Group S0016, a phase 3 randomized intergroup trial of CHOP (cyclophosphamide, hydroxydaunorubicin, oncovin, and prednisone) chemotherapy plus R-CHOP (rituximab-CHOP) compared with CHOP chemotherapy plus 131-iodine tositumomab (radioimmunotherapy [RIT]-CHOP). Subclonal TP53 mutations (median allele frequency 0.02) were found in 25% of diagnostic FL specimens and in 27% of a separate validation cohort. In the R-CHOP arm, pathogenic TP53 mutations were not associated with progression-free survival (PFS) (10-year PFS 43% vs 44%). In contrast, among patients with no detectable pathogenic TP53 mutation, RIT-CHOP was associated with a longer PFS than with R-CHOP (10-year PFS 67% vs 44%; hazard ratio = 0.49; P = .008). No relationship was detected between PFS and the extent of activation-induced cytidine deaminase (AICDA)-mediated heterogeneity. In summary, subclonal TP53 mutations are common in FL and are a distinct phenomenon from AICDA-mediated genetic heterogeneity. The absence of a detectable subclonal mutation in TP53 defined a population that particularly benefited from RIT.

Relevance of Bone Marrow Biopsies for Response Assessment in US National Cancer Institute National Clinical Trials Network Follicular Lymphoma Clinical Trials.

PURPOSE: Bone marrow biopsies (BMB) are performed before/after therapy to confirm complete response (CR) in patients with lymphoma on clinical trials. We sought to establish whether BMB add value in assessing response or predict progression-free survival (PFS) or overall survival (OS) outcomes in follicular lymphoma (FL) subjects in a large, multicenter, multitrial cohort. METHODS: Data were pooled from seven trials of 580 subjects with previously untreated FL through Alliance for Clinical Trials in Oncology (Alliance) and SWOG Cancer Research Network (SWOG) completing enrollment from 2008 to 2016. RESULTS: Only 5/580 (0.9%) had positive baseline BMB, CR on imaging, and subsequent positive BMB (P < .0001). Therefore, BMB were irrelevant to response in 99% of subjects. A sensitivity analysis of 385 FL subjects treated on an Eastern Cooperative Oncology Group study was included. In the Eastern Cooperative Oncology Group cohort, 5/385 (1.3%) had BMB that affected response assessment. Since some subjects do not undergo confirmatory BMB, we performed a landmark survival analysis from first radiologic CR with data from 580 subjects from Alliance and SWOG. Of subjects with CR on imaging (n = 187), PFS and OS were not significantly different among those with negative BMB to confirm CR (n = 47) versus those without repeat BMB (n = 140; PFS: adjusted hazard ratio, 1.10, 95% CI, 0.62 to 1.94, log-rank P = .686; OS: hazard ratio, 0.59, 95% CI, 0.23 to 1.53, log-rank P = .276). CONCLUSION: We conclude that BMB add little value to response assessment in subjects with FL treated on clinical trials and we recommend eliminating BMB from clinical trial requirements. BMB should also be removed from diagnostic guidelines for FL except in scenarios in which it may change management including confirmation of limited stage and assessment of cytopenias. This would reduce cost, patient discomfort, resource utilization, and potentially remove a barrier to trial enrollment.

Restricted survival benefit with right-censored data.

The hazard ratio is widely used to quantify treatment effects. However, it may be difficult to interpret for patients and practitioners, especially when the hazard ratio is not constant over time. Alternative measures of the treatment effects have been proposed such as the difference of the restricted mean survival times, the difference in survival proportions at some fixed follow-up time, or the net chance of a longer survival. In this paper, we propose the restricted survival benefit (RSB), a quantity that can incorporate multiple useful measurements of treatment effects. Hence, it provides a framework for a comprehensive assessment of the treatment effects. We provide estimation and inference procedures for the RSB that accommodate censored survival outcomes, using methods of the inverse-probability-censoring-weighted U$U$ -statistic and the jackknife empirical likelihood. We conduct extensive simulation studies to examine the numerical performance of the proposed method, and we analyze data from a randomized Phase III clinical trial (SWOG S0777) using the proposed method.

Biomarker-driven therapies for previously treated squamous non-small-cell lung cancer (Lung-MAP SWOG S1400): a biomarker-driven master protocol.

BACKGROUND: The Lung Cancer Master Protocol (Lung-MAP; S1400) is a completed biomarker-driven master protocol designed to address an unmet need for better therapies for squamous non-small-cell lung cancer. Lung-MAP (S1400) was created to establish an infrastructure for biomarker screening and rapid regulatory intent evaluation of targeted therapies and was the first biomarker-driven master protocol initiated with the US National Cancer Institute (NCI). METHODS: Lung-MAP (S1400) was done within the National Clinical Trials Network of the NCI using a public-private partnership. Eligible patients were aged 18 years or older, had stage IV or recurrent squamous non-small-cell lung cancer, had previously been treated with platinum-based chemotherapy, and had an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2. The study included a screening component using the FoundationOne assay (Foundation Medicine, Cambridge, MA, USA) for next-generation sequencing, and a clinical trial component with biomarker-driven substudies and non-match substudies for patients who were ineligible for biomarker-driven substudies. Patients were pre-screened and received their substudy assignment upon progression, or they were screened at progression and received their substudy assignment upon completion of testing. Patients could enrol onto additional substudies after progression on a substudy. The study is registered with ClinicalTrials.gov, NCT02154490, and all research related to Lung-MAP (S1400) is completed. FINDINGS: Between June 16, 2014, and Jan 28, 2019, 1864 patients enrolled and 1841 (98·9%) submitted tissue. 1674 (90·9%) of 1841 patients had biomarker results, and 1404 (83·9%) of 1674 patients received a substudy assignment. Of the assigned patients, 655 (46·7%) registered to a substudy. The biomarker-driven substudies evaluated taselisib (targeting PIK3CA alterations), palbociclib (cell cycle gene alterations), AZD4547 (FGFR alteration), rilotumumab plus erlotinib (MET), talazoparib (homologous recombination repair deficiency), and telisotuzumab vedotin (MET). The non-match substudies evaluated durvalumab, and nivolumab plus ipilimumab for anti-PD-1 or anti-PD-L1-naive disease, and durvalumab plus tremelimumab for anti-PD-1 or anti-PD-L1 relapsed disease. Combining data from the substudies, ten (7·0%) of 143 patients responded to targeted therapy, 53 (16·8%) of 315 patients responded to anti-PD-1 or anti-PD-L1 therapy for immunotherapy-naive disease, and three (5·4%) of 56 responded to docetaxel in the second line of therapy. Median overall survival was 5·9 months (95% CI 4·8-7·8) for the targeted therapy groups, 7·7 months (6·7-9·2) for the docetaxel groups, and 10·8 months (9·4-12·3) for the anti-PD-1 or anti-PD-L1-containing groups. Median progression-free survival was 2·5 months (95% CI 1·7-2·8) for the targeted therapy groups, 2·7 months (1·9-2·9) for the docetaxel groups, and 3·0 months (2·7-3·9) for the anti-PD-1 or anti-PD-L1-containing groups. INTERPRETATION: Lung-MAP (S1400) met its goal to quickly address biomarker-driven therapy questions in squamous non-small-cell lung cancer. In early 2019, a new screening protocol was implemented expanding to all histological types of non-small-cell lung cancer and to add focus on immunotherapy combinations for anti-PD-1 and anti-PD-L1 therapy-relapsed disease. With these changes, Lung-MAP continues to meet its goal to focus on unmet needs in the treatment of advanced lung cancers. FUNDING: US National Institutes of Health, and AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Genentech, and Pfizer through the Foundation for the National Institutes of Health.

Positron Emission Tomography-Directed Therapy for Patients With Limited-Stage Diffuse Large B-Cell Lymphoma: Results of Intergroup National Clinical Trials Network Study S1001.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) presents as a limited-stage disease in 25% to 30% of patients, with better overall survival (OS) than that for advanced-stage disease but with continuous relapse regardless of treatment approach. The preferred treatment is abbreviated rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) and radiation therapy. On the basis of promising results of positron emission tomography (PET)-directed treatment approaches, we designed a National Clinical Trials Network (NCTN) study to improve outcomes and decrease toxicity. METHODS: Patients with nonbulky (< 10 cm) stage I/II untreated DLBCL received 3 cycles of standard R-CHOP therapy and underwent a centrally reviewed interim PET/computed tomography scan (iPET). Those with a negative iPET proceeded with 1 additional cycle of R-CHOP, whereas those with a positive iPET received involved field radiation therapy followed by ibritumomab tiuxetan radioimmunotherapy. RESULTS: Of 158 patients enrolled, 132 were eligible and 128 underwent iPET, which was positive in 14 (11%) of the patients. With a median follow-up of 4.92 years (range, 1.1-7.7 years), only 6 patients progressed and 3 died as a result of lymphoma. Eleven patients died as a result of nonlymphoma causes at a median age of 80 years. The 5-year progression-free survival estimate was 87% (95% CI, 79% to 92%) and the OS estimate was 89% (95% CI, 82% to 94%), with iPET-positive and iPET-negative patients having similar outcomes. CONCLUSION: To our knowledge, S1001 is the largest prospective study in the United States of limited-stage DLBCL in the rituximab era, with the best NCTN results in this disease subset. With PET-directed therapy, 89% of the patients with a negative iPET received R-CHOP × 4, and only 11% had a positive iPET and required radiation, with both groups having excellent outcomes. The trial establishes R-CHOP × 4 alone as the new standard approach to limited-stage disease for the absolute majority of patients.

Designing precision medicine trials to yield a greater population impact.

Traditionally, a clinical trial is conducted comparing treatment to standard care for all patients. However, it could be inefficient given patients' heterogeneous responses to treatments, and rapid advances in the molecular understanding of diseases have made biomarker-based clinical trials increasingly popular. We propose a new targeted clinical trial design, termed as Max-Impact design, which selects the appropriate subpopulation for a clinical trial and aims to optimize population impact once the trial is completed. The proposed design not only gains insights on the patients who would be included in the trial but also considers the benefit to the excluded patients. We develop novel algorithms to construct enrollment rules for optimizing population impact, which are fairly general and can be applied to various types of outcomes. Simulation studies and a data example from the SWOG Cancer Research Network demonstrate the competitive performance of our proposed method compared to traditional untargeted and targeted designs.

Quantifying treatment effects using the personalized chance of longer survival.

The hazard ratio is widely used to measure or to summarize the magnitude of treatment effects, but it is justifiably difficult to interpret in a meaningful way to patients and perhaps for clinicians as well. In addition, it is most meaningful when the hazard functions are approximately proportional over time. We propose a new measure, termed personalized chance of longer survival. The measure, which quantifies the probability of living longer with one treatment over the another, accounts for individualized characteristics to directly address personalized treatment effects. Hence, the measure is patient focused, which can be used to evaluate subgroups easily. We believe it is intuitive to understand and clinically interpretable in the presence of nonproportionality. Furthermore, because it estimates the probability of living longer by some fixed amount of time, it encodes the probabilistic part of treatment effect estimation. We provide nonparametric estimation and inference procedures that can accommodate censored survival outcomes. We conduct extensive simulation studies, which characterize performance of the proposed method, and data from a large randomized Phase III clinical trial (SWOG S0819) are analyzed using the proposed method.

Robustifying Trial-Derived Optimal Treatment Rules for A Target Population.

Treatment rules based on individual patient characteristics that are easy to interpret and disseminate are important in clinical practice. Properly planned and conducted randomized clinical trials are used to construct individualized treatment rules. However, it is often a concern that trial participants lack representativeness, so it limits the applicability of the derived rules to a target population. In this work, we use data from a single trial study to propose a two-stage procedure to derive a robust and parsimonious rule to maximize the benefit in the target population. The procedure allows a wide range of possible covariate distributions in the target population, with minimal assumptions on the first two moments of the covariate distribution. The practical utility and favorable performance of the methodology are demonstrated using extensive simulations and a real data application.

Continued Risk of Relapse Independent of Treatment Modality in Limited-Stage Diffuse Large B-Cell Lymphoma: Final and Long-Term Analysis of Southwest Oncology Group Study S8736.

PURPOSE: Utility of combined-modality therapy for patients with limited-stage diffuse large B-cell lymphoma (DLBCL) was shown in the Southwest Oncology Group (SWOG) S8736 study, where three cycles of CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) plus radiotherapy (CHOP3RT) improved 5-year progression-free (PFS) and overall survival (OS) compared with eight cycles of CHOP (CHOP8). Subsequent analysis showed an unexpected overlap of the PFS curves. We aimed to confirm and investigate this observation by performing long-term analysis of SWOG S8736 and evaluating these data alongside data from similar patients receiving rituximab and CHOP3RT (SWOG S0014 study). PATIENTS AND METHODS: A subset of patients with limited-stage DLBCL randomly assigned to CHOP8 (n = 150) or CHOP3RT (n = 158) in S8736 was analyzed along with a 56-patient subset treated in S0014 for long-term PFS and OS. RESULTS: Median follow-up in S8736 was 17.7 years. In patients receiving CHOP8 and CHOP3RT, median PFS was 12.0 (95% CI, 8.8 to 14.3) and 11.1 years (95% CI, 8.9 to 14.4), respectively. There were no statistically significant differences in PFS between the groups (P = .73). Median OS was 13.0 (95% CI, 10.4 to 15.2) and 13.7 years (95% CI, 11.1 to 19.4) for patients treated with CHOP8 and CHOP3RT, respectively. Similarly, there were no statistically significant differences in OS between the groups (P = .38). With a median follow-up time 12 years in S0014, 5- and 10-year OS were 82% and 67%, respectively, with a persistent pattern of relapse despite the addition of rituximab. CONCLUSION: Although 5-year PFS and OS were improved after early analysis in patients with limited-stage DLBCL receiving CHOP3RT versus CHOP8, extended survival data showed similar PFS and OS, with continuous treatment failure. The addition of rituximab (S0014) to combined-modality therapy did not mitigate the continued relapse risk, underscoring the value of prolonged clinical trial patient observation and possible unique biology of limited-stage DLBCL.

Design of phase I combination trials: recommendations of the Clinical Trial Design Task Force of the NCI Investigational Drug Steering Committee.

Anticancer drugs are combined in an effort to treat a heterogeneous tumor or to maximize the pharmacodynamic effect. The development of combination regimens, while desirable, poses unique challenges. These include the selection of agents for combination therapy that may lead to improved efficacy while maintaining acceptable toxicity, the design of clinical trials that provide informative results for individual agents and combinations, and logistic and regulatory challenges. The phase I trial is often the initial step in the clinical evaluation of a combination regimen. In view of the importance of combination regimens and the challenges associated with developing them, the Clinical Trial Design (CTD) Task Force of the National Cancer Institute Investigational Drug Steering Committee developed a set of recommendations for the phase I development of a combination regimen. The first two recommendations focus on the scientific rationale and development plans for the combination regimen; subsequent recommendations encompass clinical design aspects. The CTD Task Force recommends that selection of the proposed regimens be based on a biologic or pharmacologic rationale supported by clinical and/or robust and validated preclinical evidence, and accompanied by a plan for subsequent development of the combination. The design of the phase I clinical trial should take into consideration the potential pharmacokinetic and pharmacodynamic interactions as well as overlapping toxicity. Depending on the specific hypothesized interaction, the primary endpoint may be dose optimization, pharmacokinetics, and/or pharmacodynamics (i.e., biomarker).

Genetic polymorphisms in oxidative stress-related genes are associated with outcomes following treatment for aggressive B-cell non-Hodgkin lymphoma.

Variable survival outcomes are seen following treatment for aggressive non-Hodgkin lymphoma (NHL). This study examined whether outcomes for aggressive B-cell NHL are associated with single nucleotide polymorphisms (SNPs) in oxidative stress-related genes, which can alter drug metabolism and immune responses. Genotypes for 53 SNPs in 29 genes were determined for 337 patients given anthracycline-based therapies. Their associations with progression-free survival (PFS) and overall survival (OS) were estimated by Cox proportional hazard regression; associations with hematologic toxicity were estimated by logistic regression. To validate the findings, the top three SNPs were tested in an independent cohort of 572 DLBCL patients. The top SNPs associated with PFS in the discovery cohort were the rare homozygotes for MPO rs2243828 (hazard ratio [HR] = 1.87, 95% confidence interval [CI] = 1.14-3.06, P = 0.013), AKR1C3 rs10508293 (HR = 2.09, 95% CI = 1.28-3.41, P = 0.0032) and NCF4 rs1883112 (HR = 0.66, 95% CI = 0.43-1.02, P = 0.06). The association of the NCF4 SNP with PFS was replicated in the validation dataset (HR = 0.66, 95% CI = 0.44-1.01, P = 0.05) and the meta-analysis was significant (HR = 0.66, 95% CI = 0.49-0.89, P < 0.01). The association of the MPO SNP was attenuated in the validation dataset, while the meta-analysis remained significant (HR = 1.64, 95% CI = 1.12-2.41). These two SNPs showed similar trends with OS in the meta-analysis (for NCF4, HR = 0.72, 95% CI = 0.51-1.02, P = 0.07 and for MPO, HR = 2.06, 95% CI = 1.36-3.12, P < 0.01). In addition, patients with the rare homozygote of the NCF4 SNP had an increased risk of hematologic toxicity. We concluded that genetic variations in NCF4 may contribute to treatment outcomes for patients with aggressive NHL.

Cure models as a useful statistical tool for analyzing survival.

Cure models are a popular topic within statistical literature but are not as widely known in the clinical literature. Many patients with cancer can be long-term survivors of their disease, and cure models can be a useful tool to analyze and describe cancer survival data. The goal of this article is to review what a cure model is, explain when cure models can be used, and use cure models to describe multiple myeloma survival trends. Multiple myeloma is generally considered an incurable disease, and this article shows that by using cure models, rather than the standard Cox proportional hazards model, we can evaluate whether there is evidence that therapies at the University of Arkansas for Medical Sciences induce a proportion of patients to be long-term survivors.

Distribution-free inference on contrasts of arbitrary summary measures of survival.

We present an approach for inference on contrasts of clinically meaningful functionals of a survivor distribution (e.g., restricted mean, quantiles) that can avoid strong parametric or semiparametric assumptions on the underlying structure of the data. In this multistage approach, we first use an adaptive predictive model to estimate conditional survival distributions based on covariates. We then estimate nonparametrically one or more functionals of survival from the covariate-specific survival curves and evaluated contrasts of those functionals. We find that the use of an adaptive nonparametric tree-based predictive model leads to minimal loss in precision when semiparametric assumptions hold and provides marked improvement in accuracy when those assumptions are invalid. Therefore, this work as a whole supports the use of survival summaries appropriate to a given medical application, whether that be, for example, the median or 75th percentile in some settings or perhaps a restricted mean in others. The approach is also compared with the Mayo R score for primary biliary cirrhosis prognosis.

A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.

BACKGROUND: Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL). Often, data are analyzed with genes classified by whether they fall above or below the median expression level. We sought to determine whether examining multiple cut-points might be a more powerful technique to investigate the association of gene expression with outcome. METHODOLOGY/PRINCIPAL FINDINGS: We explored gene expression profiling data using variable cut-point analysis for 36 genes with reported prognostic value in DLBCL. We plotted two-group survival logrank test statistics against corresponding cut-points of the gene expression levels and smooth estimates of the hazard ratio of death versus gene expression levels. To facilitate comparisons we also standardized the expression of each of the genes by the fraction of patients that would be identified by any cut-point. A multiple comparison adjusted permutation p-value identified 3 different patterns of significance: 1) genes with significant cut-point points below the median, whose loss is associated with poor outcome (e.g. HLA-DR); 2) genes with significant cut-points above the median, whose over-expression is associated with poor outcome (e.g. CCND2); and 3) genes with significant cut-points on either side of the median, (e.g. extracellular molecules such as FN1). CONCLUSIONS/SIGNIFICANCE: Variable cut-point analysis with permutation p-value calculation can be used to identify significant genes that would not otherwise be identified with median cut-points and may suggest biological patterns of gene effects.