Follow-up from the A041202 study shows continued efficacy of ibrutinib regimens for older adults with CLL.

ABSTRACT: A041202 (NCT01886872) is a phase 3 study comparing bendamustine plus rituximab (BR) with ibrutinib and the combination of ibrutinib plus rituximab (IR) in previously untreated older patients with chronic lymphocytic leukemia (CLL). The initial results showed that ibrutinib-containing regimens had superior progression-free survival (PFS) and rituximab did not add additional benefits. Here we present an updated analysis. With a median follow-up of 55 months, the median PFS was 44 months (95% confidence interval [CI], 38-54) for BR and not yet reached in either ibrutinib-containing arm. The 48-month PFS estimates were 47%, 76%, and 76% for BR, ibrutinib, and IR, respectively. The benefit of ibrutinib regimens over chemoimmunotherapy was consistent across subgroups of patients defined by TP53 abnormalities, del(11q), complex karyotype, and immunoglobulin heavy chain variable region (IGHV). No significant interaction effects were observed between the treatment arm and del(11q), the complex karyotype, or IGHV. However, a greater difference in PFS was observed among the patients with TP53 abnormalities. There was no difference in the overall survival. Notable adverse events with ibrutinib included atrial fibrillation (afib) and hypertension. Afib was observed in 11 patients (pts) on BR (3%) and 67 pts on ibrutinib (18%). All-grade hypertension was observed in 95 pts on BR (27%) and 263 pts on ibrutinib (55%). These data show that ibrutinib regimens prolong PFS compared with BR for older patients with treatment-naïve CLL. These benefits were observed across subgroups, including high-risk groups. Strikingly, within the ibrutinib arms, there was no inferior PFS for patients with abnormalities in TP53, the highest risk feature observed in CLL. These data continue to demonstrate the efficacy of ibrutinib in treatment-naïve CLL.

Transforming the oncology data paradigm by creating, capturing, and retrieving structured cancer data at the point of care: A Mayo Clinic pilot.

INTRODUCTION: Structured data capture requires defined languages such as minimal Common Oncology Data Elements (mCODE). This pilot assessed the feasibility of capturing 5 mCODE categories (stage, disease status, performance status (PS), intent of therapy and intent to change therapy). METHODS: A tool (SmartPhrase) using existing and custom structured data elements was Built to capture 4 data categories (disease status, PS, intent of therapy and intent to change therapy) typically documented as free-text within notes. Existing functionality for stage was supported by the Build. Participant survey data, presence of data (per encounter), and time in chart were collected prior to go-live and repeat timepoints. The anticipated outcome was capture of >50% sustained over time without undue burden. RESULTS: Pre-intervention (5-weeks before go-live), participants had 1390 encounters (1207 patients). The median percent capture across all participants was 32% for stage; no structured data was available for other categories pre-intervention. During a 6-month pilot with 14 participants across three sites, 4995 encounters (3071 patients) occurred. The median percent capture across all participants and all post-intervention months increased to 64% for stage and 81%-82% for the other data categories post-intervention. No increase in participant time in chart was noted. Participants reported that data were meaningful to capture. CONCLUSIONS: Structured data can be captured (1) in real-time, (2) sustained over time without (3) undue provider burden using note-based tools. Our system is expanding the pilot, with integration of these data into clinical decision support, practice dashboards and potential for clinical trial matching.

Statistical Considerations and Software for Designing Sequential, Multiple Assignment, Randomized Trials (SMART) with a Survival Final Endpoint.

Sequential, multiple assignment, randomized trial (SMART) designs are appropriate for comparing adaptive treatment interventions, in which intermediate outcomes (called tailoring variables) guide subsequent treatment decisions for individual patients. Within a SMART design, patients may be re-randomized to subsequent treatments following the outcomes of their intermediate assessments. In this paper, we provide an overview of statistical considerations necessary to design and implement a two-stage SMART design with a binary tailoring variable and a survival final endpoint. A chronic lymphocytic leukemia trial with a final endpoint of progression-free survival is used as an example for the simulations to assess how design parameters, including, choice of randomization ratios for each stage of randomization, and response rates of the tailoring variable affect the statistical power. We assess the choice of weights from restricted re-randomization on data analyses and appropriate hazard rate assumptions. Specifically, for a given first-stage therapy and prior to the tailoring variable assessment, we assume equal hazard rates for all patients randomized to a treatment arm. After the tailoring variable assessment, individual hazard rates are assumed for each intervention path. Simulation studies demonstrate that the response rate of the binary tailoring variable impacts power as it directly impacts the distribution of patients. We also confirm that when the first stage randomization is 1:1, it is not necessary to consider the first stage randomization ratio when applying the weights. We provide an R-shiny application for obtaining power for a given sample size for SMART designs.

Impact of NPM1/FLT3-ITD genotypes defined by the 2017 European LeukemiaNet in patients with acute myeloid leukemia.

Patients with acute myeloid leukemia (AML) harboring FLT3 internal tandem duplications (ITDs) have poor outcomes, in particular AML with a high (≥0.5) mutant/wild-type allelic ratio (AR). The 2017 European LeukemiaNet (ELN) recommendations defined 4 distinct FLT3-ITD genotypes based on the ITD AR and the NPM1 mutational status. In this retrospective exploratory study, we investigated the prognostic and predictive impact of the NPM1/FLT3-ITD genotypes categorized according to the 2017 ELN risk groups in patients randomized within the RATIFY trial, which evaluated the addition of midostaurin to standard chemotherapy. The 4 NPM1/FLT3-ITD genotypes differed significantly with regard to clinical and concurrent genetic features. Complete ELN risk categorization could be done in 318 of 549 trial patients with FLT3-ITD AML. Significant factors for response after 1 or 2 induction cycles were ELN risk group and white blood cell (WBC) counts; treatment with midostaurin had no influence. Overall survival (OS) differed significantly among ELN risk groups, with estimated 5-year OS probabilities of 0.63, 0.43, and 0.33 for favorable-, intermediate-, and adverse-risk groups, respectively (P < .001). A multivariate Cox model for OS using allogeneic hematopoietic cell transplantation (HCT) in first complete remission as a time-dependent variable revealed treatment with midostaurin, allogeneic HCT, ELN favorable-risk group, and lower WBC counts as significant favorable factors. In this model, there was a consistent beneficial effect of midostaurin across ELN risk groups.

Ibrutinib Regimens versus Chemoimmunotherapy in Older Patients with Untreated CLL.

BACKGROUND: Ibrutinib has been approved by the Food and Drug Administration for the treatment of patients with untreated chronic lymphocytic leukemia (CLL) since 2016 but has not been compared with chemoimmunotherapy. We conducted a phase 3 trial to evaluate the efficacy of ibrutinib, either alone or in combination with rituximab, relative to chemoimmunotherapy. METHODS: Patients 65 years of age or older who had untreated CLL were randomly assigned to receive bendamustine plus rituximab, ibrutinib, or ibrutinib plus rituximab. The primary end point was progression-free survival. The Alliance Data and Safety Monitoring Board made the decision to release the data after the protocol-specified efficacy threshold had been met. RESULTS: A total of 183 patients were assigned to receive bendamustine plus rituximab, 182 to receive ibrutinib, and 182 to receive ibrutinib plus rituximab. Median progression-free survival was reached only with bendamustine plus rituximab. The estimated percentage of patients with progression-free survival at 2 years was 74% with bendamustine plus rituximab and was higher with ibrutinib alone (87%; hazard ratio for disease progression or death, 0.39; 95% confidence interval [CI], 0.26 to 0.58; P<0.001) and with ibrutinib plus rituximab (88%; hazard ratio, 0.38; 95% CI, 0.25 to 0.59; P<0.001). There was no significant difference between the ibrutinib-plus-rituximab group and the ibrutinib group with regard to progression-free survival (hazard ratio, 1.00; 95% CI, 0.62 to 1.62; P=0.49). With a median follow-up of 38 months, there was no significant difference among the three treatment groups with regard to overall survival. The rate of grade 3, 4, or 5 hematologic adverse events was higher with bendamustine plus rituximab (61%) than with ibrutinib or ibrutinib plus rituximab (41% and 39%, respectively), whereas the rate of grade 3, 4, or 5 nonhematologic adverse events was lower with bendamustine plus rituximab (63%) than with the ibrutinib-containing regimens (74% with each regimen). CONCLUSIONS: Among older patients with untreated CLL, treatment with ibrutinib was superior to treatment with bendamustine plus rituximab with regard to progression-free survival. There was no significant difference between ibrutinib and ibrutinib plus rituximab with regard to progression-free survival. (Funded by the National Cancer Institute and Pharmacyclics; ClinicalTrials.gov number, NCT01886872 .).

Impact of the COVID-19 Pandemic on Cancer Clinical Trials.

The COVID-19 pandemic has had widespread impact on healthcare, resulting in modifications to how we perform cancer research, including clinical trials for cancer. The impact of some healthcare workers and study coordinators working remotely and patients minimizing visits to medical facilities impacted clinical trial participation. Clinical trial accrual dropped at the onset of the pandemic, with improvement over time. Adjustments were made to some trial protocols, allowing telephone or video-enabled consent. Certain study activities were permitted to be performed by local healthcare providers or at local laboratories to maximize patients' ability to continue on study during these challenging times. We discuss the impact of COVID-19 on cancer clinical trials and changes at the local, cooperative group, and national level.

Understanding Verbosity: Funding Source and the Length of Consent Forms for Cancer Clinical Trials.

Consent forms are an important educational tool that helps cancer patients decide on whether or not to enroll on a clinical trial, but wordiness potentially detracts from their educational value. This single-institution study examined word counts of consent forms for all phase I, II, and III solid tumor clinical trials between 2004 and 2010. Consent forms were categorized by trial funding source: (1) pharmaceutical company; (2) National Clinical Trials Network (NCTN); (3) R01- or other non-government grants; and (4) mixed (funding from multiple sources). Three hundred fifteen consent forms were studied; these included 106 (34%) pharmaceutical company; 145 (46%) NCTN; 44 (14%) R01 type; and 20 (6%) mixed. The overall median word count was 5129 words per consent form (interquartile range (IQR) range, 4226 to 6695). The median word counts per consent form (IQR) were 5648 (4814, 6803), 5243 (4139, 6932), 4365 (3806, 5124), and 4319 (3862, 5944), respectively, based on the above funding sources, showing that pharmaceutical company trial consent forms had the highest median word count. Of note, phase of trial was associated with consent form length (phase III were wordier), and consent forms manifested a consistent increase in wordiness over time. These observations underscore a timely need to find ways to limit the verbosity of consent forms, particularly in those from pharmaceutical company trials.

A Phase II Study of Pazopanib in Patients with Malignant Pleural Mesothelioma: NCCTG N0623 (Alliance).

PURPOSE: Preclinical and clinical data have shown promise in using antiangiogenic agents to treat malignant pleural mesothelioma (MPM). We conducted this phase II study to evaluate the efficacy and toxicity of single-agent pazopanib in patients with MPM. MATERIALS AND METHODS: Patients with MPM who had received 0-1 prior chemotherapy regimens were eligible to receive pazopanib at a dose of 800 mg daily. The primary endpoint was progression-free survival rate at 6 months (PFS6), with a preplanned interim analysis for futility. Secondary endpoints included overall survival (OS), PFS, adverse events assessment and clinical benefit (complete response, partial response [PR], and stable disease [SD]). RESULTS: Thirty-four evaluable patients were enrolled, with a median age of 73 years (49-84). The trial was closed early because of lack of efficacy at the preplanned interim analysis. Only 8 patients (28.6%; 95% confidence interval [CI], 13.2-48.7%) in the first 28 evaluable were progression-free at 6 months. PFS6 was 32.4% (95% CI, 17.4-50.5). There were 2 PR (5.9%) and 16 SD (47.1%). The overall median PFS and OS were 4.2 months (95% CI, 2.0-6.0) and 11.5 months (95% CI: 5.3-18.2), respectively. The median PFS and OS for the previously untreated patients was 5.4 months (95% CI, 2.7-8.5) and 16.6 months (95% CI, 6.6-30.6), respectively; and 2.0 months (95% CI, 1.3-4.2) and 5.0 months (95% CI: 3.0-11.9), respectively, for the previously treated patients. Grade 3 or higher adverse events were observed in 23 patients (67.6%). CONCLUSION: Single-agent pazopanib was poorly tolerated in patients with MPM. The primary endpoint of PFS6 was not achieved in the current study. ClinicalTrials.gov identification number. NCT00459862. IMPLICATIONS FOR PRACTICE: Single-agent pazopanib did not meet its endpoint in this phase II trial in malignant mesothelioma. Pazopanib is well tolerated in mesothelioma patients with a manageable toxicity profile. There is a need to better identify signals of angiogenesis that can be targeted in mesothelioma. Encouraging findings in frontline treatment warrant further investigations in combination with chemotherapy or immunotherapy.

Midostaurin plus Chemotherapy for Acute Myeloid Leukemia with a FLT3 Mutation.

BACKGROUND: Patients with acute myeloid leukemia (AML) and a FLT3 mutation have poor outcomes. We conducted a phase 3 trial to determine whether the addition of midostaurin - an oral multitargeted kinase inhibitor that is active in patients with a FLT3 mutation - to standard chemotherapy would prolong overall survival in this population. METHODS: We screened 3277 patients, 18 to 59 years of age, who had newly diagnosed AML for FLT3 mutations. Patients were randomly assigned to receive standard chemotherapy (induction therapy with daunorubicin and cytarabine and consolidation therapy with high-dose cytarabine) plus either midostaurin or placebo; those who were in remission after consolidation therapy entered a maintenance phase in which they received either midostaurin or placebo. Randomization was stratified according to subtype of FLT3 mutation: point mutation in the tyrosine kinase domain (TKD) or internal tandem duplication (ITD) mutation with either a high ratio (>0.7) or a low ratio (0.05 to 0.7) of mutant to wild-type alleles (ITD [high] and ITD [low], respectively). Allogeneic transplantation was allowed. The primary end point was overall survival. RESULTS: A total of 717 patients underwent randomization; 360 were assigned to the midostaurin group, and 357 to the placebo group. The FLT3 subtype was ITD (high) in 214 patients, ITD (low) in 341 patients, and TKD in 162 patients. The treatment groups were well balanced with respect to age, race, FLT3 subtype, cytogenetic risk, and blood counts but not with respect to sex (51.7% in the midostaurin group vs. 59.4% in the placebo group were women, P=0.04). Overall survival was significantly longer in the midostaurin group than in the placebo group (hazard ratio for death, 0.78; one-sided P=0.009), as was event-free survival (hazard ratio for event or death, 0.78; one-sided P=0.002). In both the primary analysis and an analysis in which data for patients who underwent transplantation were censored, the benefit of midostaurin was consistent across all FLT3 subtypes. The rate of severe adverse events was similar in the two groups. CONCLUSIONS: The addition of the multitargeted kinase inhibitor midostaurin to standard chemotherapy significantly prolonged overall and event-free survival among patients with AML and a FLT3 mutation. (Funded by the National Cancer Institute and Novartis; ClinicalTrials.gov number, NCT00651261 .).

An adaptive multi-stage phase I dose-finding design incorporating continuous efficacy and toxicity data from multiple treatment cycles.

Phase I designs traditionally use the dose-limiting toxicity (DLT), a binary endpoint from the first treatment cycle, to identify the maximum-tolerated dose (MTD) assuming a monotonically increasing relationship between dose and efficacy. In this article, we establish a general framework for a multi-stage adaptive design where we jointly model a continuous efficacy outcome and continuous/quasi-continuous toxicity endpoints from multiple treatment cycles. The normalized Total Toxicity Profile (nTTP) is used as an illustration for quasi-continuous toxicity endpoints, and we replace DLT with nTTP to take into account multiple grades and types of toxicities. In addition, the proposed design accommodates non-monotone dose-efficacy relationships, and longitudinal toxicity data in effort to capture the adverse events from multiple cycles. Stage 1 of our design uses toxicity data to perform dose-escalation and identify a set of initially allowable (safe) doses; stage 2 of our design incorporates an efficacy outcome to update the set of allowable doses for each new cohort and randomizes the new cohort of patients to the allowable doses with emphasis towards those with higher predicted efficacy. Stage 3 uses all data from all treated patients at the end of the trial to make final recommendations. Simulations showed that the design had a high probability of making the correct dose selection and good overdose control across various dose-efficacy and dose-toxicity scenarios. In addition, the proposed design allows for early termination when all doses are too toxic. To our best knowledge, the proposed dual-endpoint dose-finding design is the first such study to incorporate multiple cycles of toxicities and a continuous efficacy outcome.

Application of multi-state models in cancer clinical trials.

Background/aims The goal of this article is to illustrate the utility of multi-state models in cancer clinical trials. Our specific aims are to describe multi-state models and how they differ from standard survival methods, to illustrate how multi-state models can facilitate deeper understanding of the treatment effect on multiple paths along the disease process that patients could experience in cancer clinical trials, to explain the differences between multi-state models and time-dependent Cox models, and to briefly describe available software to conduct such analyses. Methods Data from 717 newly diagnosed acute myeloid leukemia patients who enrolled in the CALGB 10603 trial were used as an illustrative example. The current probability-in-state was estimated using the Aalen-Johansen estimator. The restricted mean time in state was calculated as the area under the probability-in-state curves. Cox-type regression was used to evaluate the effect of midostaurin on the various clinical paths. Simulation was conducted using a newly constructed shiny application. All analyses were performed using the R software. Results Multi-state model analyses of CALGB 10603 suggested that the overall improvement in survival with midostaurin seen in the primary analysis possibly resulted from a higher complete remission rate in combination with a lower risk of relapse and of death after complete remission in patients treated with midostaurin. Simulation results, in a three-state illness-death without recovery model, demonstrate that multi-state models and time-dependent Cox models evaluate treatment effects from different frameworks. Conclusion Multi-state models allow detailed evaluation of treatment effects in complex clinical trial settings where patients can experience multiple paths between study enrollment and the final outcome. Multi-state models can be used as a complementary tool to standard survival analyses to provide deeper insights to the effects of treatment in trial settings with complex disease process.

Definitions and statistical properties of master protocols for personalized medicine in oncology.

Within the field of cancer research, discovery of biomarkers and genetic mutations that are potentially predictive of treatment benefit is motivating a paradigm shift in how cancer clinical trials are conducted. In this review, we provide an overview of the class of trials known as "master protocols," including basket trials, umbrella trials, and platform trials. For each, we describe standardized terminology, provide a motivating example with modeling details and decision rules, and discuss statistical advantages and limitations. We conclude with a discussion of general statistical considerations and challenges encountered across these types of trials.

A Bayesian dose-finding design incorporating toxicity data from multiple treatment cycles.

Phase I oncology trials are designed to identify a safe dose with an acceptable toxicity profile. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle, although patients continue to receive treatment for multiple cycles. In addition, the toxicity data from multiple types and grades are typically summarized into a single binary outcome of dose-limiting toxicity. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades. In this work, we propose to account for longitudinal repeated measures of total toxicity profile over multiple treatment cycles, accounting for cumulative toxicity during dosing-finding. A linear mixed model was utilized in the Bayesian framework, with addition of Bayesian risk functions for decision-making in dose assignment. The performance of this design is evaluated using simulation studies and compared with the previously proposed quasi-likelihood continual reassessment method (QLCRM) design. Twelve clinical scenarios incorporating four different locations of maximum tolerated dose and three different time trends (decreasing, increasing, and no effect) were investigated. The proposed repeated measures design was comparable with the QLCRM when only cycle 1 data were utilized in dose-finding; however, it demonstrated an improvement over the QLCRM when data from multiple cycles were used across all scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

Repeated measures dose-finding design with time-trend detection in the presence of correlated toxicity data.

BACKGROUND: Phase I trials are designed to determine the safety, tolerability, and recommended phase 2 dose of therapeutic agents for subsequent testing. The dose-finding paradigm has thus traditionally focused on identifying the maximum tolerable dose of an agent or combination therapy under the assumption that there is a non-decreasing relationship between dose-toxicity and dose-efficacy. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades experienced in the first cycle. More recently, this was extended to a repeated measures design based on the total toxicity profile to account for longitudinal toxicities over multiple treatment cycles in the absence of within-patient correlation. METHODS: In this work, we propose to extend the design in the presence of within-patient correlation. Furthermore, we provide a framework to detect a toxicity time trend (toxicity increasing, decreasing, or stable) over multiple treatment cycles. We utilize a linear mixed model in the Bayesian framework, with the addition of Bayesian risk functions for decision-making in dose assignment. RESULTS: The performance of this design was evaluated using simulation studies and real data from a phase I trial. We demonstrated that using available toxicity data from all cycles of treatment improves the accuracy of maximum tolerated dose identification and allows for the detection of a time trend. The performance is consistent regardless of the strength of the within-patient correlation. In addition, the use of a quasi-continuous total toxicity profile score significantly increased the power to detect time trends compared to when binary data only were used. CONCLUSION: The increased interest in molecularly targeted agents and immunotherapies in oncology necessitates innovative phase I study designs. Our proposed framework provides a tool to tackle some of the challenges presented by these novel agents, specifically through the ability to understand patterns of toxicity over time, which is important in the cases of cumulative or late toxicities.

Metformin does not reduce markers of cell proliferation in esophageal tissues of patients with Barrett's esophagus.

BACKGROUND & AIMS: Obesity is associated with neoplasia, possibly via insulin-mediated cell pathways that affect cell proliferation. Metformin has been proposed to protect against obesity-associated cancers by decreasing serum insulin. We conducted a randomized, double-blind, placebo-controlled, phase 2 study of patients with Barrett's esophagus (BE) to assess the effect of metformin on phosphorylated S6 kinase (pS6K1), a biomarker of insulin pathway activation. METHODS: Seventy-four subjects with BE (mean age, 58.7 years; 58 men [78%; 52 with BE >2 cm [70%]) were recruited through 8 participating organizations of the Cancer Prevention Network. Participants were randomly assigned to groups given metformin daily (increasing to 2000 mg/day by week 4, n = 38) or placebo (n = 36) for 12 weeks. Biopsy specimens were collected at baseline and at week 12 via esophagogastroduodenoscopy. We calculated and compared percent changes in median levels of pS6K1 between subjects given metformin vs placebo as the primary end point. RESULTS: The percent change in median level of pS6K1 did not differ significantly between groups (1.4% among subjects given metformin vs -14.7% among subjects given placebo; 1-sided P = .80). Metformin was associated with an almost significant reduction in serum levels of insulin (median -4.7% among subjects given metformin vs 23.6% increase among those given placebo, P = .08) as well as in homeostatic model assessments of insulin resistance (median -7.2% among subjects given metformin vs 38% increase among those given placebo, P = .06). Metformin had no effects on cell proliferation (on the basis of assays for KI67) or apoptosis (on the basis of levels of caspase 3). CONCLUSIONS: In a chemoprevention trial of patients with BE, daily administration of metformin for 12 weeks, compared with placebo, did not cause major reductions in esophageal levels of pS6K1. Although metformin reduced serum levels of insulin and insulin resistance, it did not discernibly alter epithelial proliferation or apoptosis in esophageal tissues. These findings do not support metformin as a chemopreventive agent for BE-associated carcinogenesis. ClinicalTrials.gov number, NCT01447927.

High-Dose Glucocorticoids for Treating Sudden Hearing Loss: Cart before the Horse?

Hearing impairment is the most common sensory deficit. It affects 2 to 3 of 1000 newborns and nearly 50% of adults 75 years of age and older in the United States.1 Idiopathic sudden sensorineural hearing loss (ISSNHL) is characterized by an abrupt hearing loss requiring immediate diagnosis and treatment. Systemic glucocorticoids are widely used as the primary treatment for ISSNHL,2 but no head-to-head comparisons of the effectiveness and risk profiles of high doses over a more commonly used lower dose of glucocorticoids have been conducted to inform standard-of-care practice.

A combination of esomeprazole and aspirin reduces tissue concentrations of prostaglandin E(2) in patients with Barrett's esophagus.

UNLABELLED: BACKGROUND& AIMS: Proton pump inhibitors and nonsteroidal anti-inflammatory drugs might prevent esophageal adenocarcinoma in patients with Barrett's esophagus (BE), but there are limited data from clinical trials to support this concept. We conducted a randomized, double-blind, placebo-controlled, phase 2 trial to assess the effects of the combination of aspirin (3 different doses) and esomeprazole on tissue concentrations of prostaglandin (PG) E(2) in patients with BE with no dysplasia or low-grade dysplasia. METHODS: Participants were recruited through the multicenter Cancer Prevention Network and randomly assigned to groups that were given 40 mg esomeprazole twice daily in combination with an aspirin placebo once daily (arm A; n = 30), with 81 mg aspirin once daily (arm B; n = 47), or with 325 mg aspirin once daily (arm C; n = 45) for 28 days. We collected esophageal biopsy specimens before and after the intervention period to determine the absolute change in mean concentration of PGE(2) (the primary end point). RESULTS: Based on data from 114 patients, baseline characteristics were similar among groups. The absolute mean tissue concentration of PGE(2) was reduced by 67.6 ± 229.68 pg/mL in arm A, 123.9 ± 284.0 pg/mL in arm B (P = .10 vs arm A), and 174.9 ± 263.62 pg/mL in arm C (P = .02 vs arm A). CONCLUSIONS: In combination with esomeprazole, short-term administration of higher doses of aspirin, but not lower doses or no aspirin, significantly reduced tissue concentrations of PGE(2) in patients with BE with either no dysplasia or low-grade dysplasia. These data support further evaluation of higher doses of aspirin and esomeprazole to prevent esophageal adenocarcinoma in these patients. Clinical trial registration number NCT00474903.

Pomalidomide plus low-dose dexamethasone in myeloma refractory to both bortezomib and lenalidomide: comparison of 2 dosing strategies in dual-refractory disease.

Pomalidomide at doses of 2 or 4 mg/d has demonstrated excellent activity in patients with multiple myeloma (MM). We opened 2 sequential phase 2 trials using the pomalidomide with weekly dexamethasone (Pom/dex) regimen at differing doses to study the efficacy of this regimen in patients who have failed both lenalidomide and bortezomib. Pomalidomide was given orally 2 or 4 mg daily with dexamethasone 40 mg weekly. Thirty-five patients were enrolled in each cohort. Confirmed responses in the 2-mg cohort consisted of very good partial response (VGPR) in 5 (14%), partial response (PR) in 4 (11%), minor response (MR) in 8 (23%) for an overall response rate of 49%. In the 4-mg cohort, confirmed responses consisted of complete response (CR) in 1 (3%), VGPR in 3 (9%), PR in 6 (17%), MR in 5 (14%) for an overall response rate of 43%. Overall survival at 6 months is 78% and 67% in the 2- and 4-mg cohort, respectively. Myelosuppression was the most common toxicity. This nonrandomized data suggests no advantage for 4 mg over the 2 mg daily. Pomalidomide overcomes resistance in myeloma refractory to both lenalidomide and bortezomib. This trial is registered at http://ClinicalTrials.gov, number NCT00558896.