Feasibility of using real-world data to emulate substance use disorder clinical trials: a cross-sectional study.

INTRODUCTION: Real-world evidence is receiving considerable attention as a way to evaluate the efficacy and safety of medical products for substance use disorders (SUDs). However, the feasibility of using real-world data (RWD) to emulate clinical trials evaluating treatments for SUDs is uncertain. The aim of this study is to identify the number of clinical trials evaluating treatments for SUDs with reported results that could be feasibly emulated using observational data from contemporary insurance claims and/or electronic health record (EHR) data. METHODS: In this cross-sectional study, all phase 2-4 trials evaluating treatments for SUDs registered on ClinicalTrials.gov with reported results were identified. Each trial was evaluated to determine if the indications, interventions, at least 80% of eligibility criteria, comparators, and primary end points could be ascertained using contemporarily available administrative claims and/or structured EHR data. RESULTS: There were 272 SUD trials on ClinicalTrials.gov with reported results. Of these, when examining feasibility using contemporarily available administrative claims and/or structured EHR data, 262 (96.3%) had indications that were ascertainable; 194 (71.3%) had interventions that were ascertainable; 21 (7.7%) had at least 80% of eligibility criteria that were ascertainable; 17 (6.3%) had active comparators that were ascertainable; and 61 (22.4%) had primary end points that were ascertainable. In total, there were no trials for which all 5 characteristics were ascertainable using contemporarily available administrative claims and/or structured EHR data. When considering placebo comparators as ascertainable, there were 6 (2.2%) trials that had all 5 key characteristics classified as ascertainable from contemporarily available administrative claims and/or structured EHR data. CONCLUSIONS: No trials evaluating treatments for SUDs could be feasibly emulated using contemporarily available RWD, demonstrating a need for an increase in the resolution of data capture within a public health system to facilitate trial emulation.

Adaptive designs were primarily used but inadequately reported in early phase drug trials.

BACKGROUND: Faced with the high cost and limited efficiency of classical randomized controlled trials, researchers are increasingly applying adaptive designs to speed up the development of new drugs. However, the application of adaptive design to drug randomized controlled trials (RCTs) and whether the reporting is adequate are unclear. Thus, this study aimed to summarize the epidemiological characteristics of the relevant trials and assess their reporting quality by the Adaptive designs CONSORT Extension (ACE) checklist. METHODS: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov from inception to January 2020. We included drug RCTs that explicitly claimed to be adaptive trials or used any type of adaptative design. We extracted the epidemiological characteristics of included studies to summarize their adaptive design application. We assessed the reporting quality of the trials by Adaptive designs CONSORT Extension (ACE) checklist. Univariable and multivariable linear regression models were used to the association of four prespecified factors with the quality of reporting. RESULTS: Our survey included 108 adaptive trials. We found that adaptive design has been increasingly applied over the years, and was commonly used in phase II trials (n = 45, 41.7%). The primary reasons for using adaptive design were to speed the trial and facilitate decision-making (n = 24, 22.2%), maximize the benefit of participants (n = 21, 19.4%), and reduce the total sample size (n = 15, 13.9%). Group sequential design (n = 63, 58.3%) was the most frequently applied method, followed by adaptive randomization design (n = 26, 24.1%), and adaptive dose-finding design (n = 24, 22.2%). The proportion of adherence to the ACE checklist of 26 topics ranged from 7.4 to 99.1%, with eight topics being adequately reported (i.e., level of adherence ≥ 80%), and eight others being poorly reported (i.e., level of adherence ≤ 30%). In addition, among the seven items specific for adaptive trials, three were poorly reported: accessibility to statistical analysis plan (n = 8, 7.4%), measures for confidentiality (n = 14, 13.0%), and assessments of similarity between interim stages (n = 25, 23.1%). The mean score of the ACE checklist was 13.9 (standard deviation [SD], 3.5) out of 26. According to our multivariable regression analysis, later published trials (estimated ß = 0.14, p < 0.01) and the multicenter trials (estimated ß = 2.22, p < 0.01) were associated with better reporting. CONCLUSION: Adaptive design has shown an increasing use over the years, and was primarily applied to early phase drug trials. However, the reporting quality of adaptive trials is suboptimal, and substantial efforts are needed to improve the reporting.

Improved mortality analysis in early-phase dose-ranging clinical trials for emergency medical diseases using Bayesian time-to-event models with active comparators.

Emergency medical diseases (EMDs) are the leading cause of death worldwide. A time-to-death analysis is needed to accurately identify the risks and describe the pattern of an EMD because the mortality rate can peak early and then decline. Dose-ranging Phase II clinical trials are essential for developing new therapies for EMDs. However, most dose-finding trials do not analyze mortality as a time-to-event endpoint. We propose three Bayesian dose-response time-to-event models for a secondary mortality analysis of a clinical trial: a two-group (active treatment vs control) model, a three-parameter sigmoid EMAX model, and a hierarchical EMAX model. The study also incorporates one specific active treatment as an active comparator in constructing three new models. We evaluated the performance of these six models and a very popular independent model using simulated data motivated by a randomized Phase II clinical trial focused on identifying the most effective hyperbaric oxygen dose to achieve favorable functional outcomes in patients with severe traumatic brain injury. The results show that the three-group, EMAX, and EMAX model with an active comparator produce the smallest averaged mean squared errors and smallest mean absolute biases. We provide a new approach for time-to-event analysis in early-phase dose-ranging clinical trials for EMDs. The EMAX model with an active comparator can provide valuable insights into the mortality analysis of new EMDs or other conditions that have changing risks over time. The restricted mean survival time, a function of the model's hazards, is recommended for displaying treatment effects for EMD research.

Race and Ethnicity Representation in Phase 2/3 Oncology Clinical Trial Publications: A Systematic Review.

Importance: The five 1997 Office of Management and Budget races in the US include American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White, with Hispanic ethnicity. Despite the Affordable Care Act mandating Office of Management and Budget-based collecting and reporting standards, race and ethnicity publishing in medical journals is inconsistent, despite being necessary to achieve health equity. Objective: To quantify race and ethnicity reporting rates and calculate representation quotients (RQs) in published oncology clinical trials. Evidence Review: In this systematic review, PubMed and Embase were queried for phase 2/3 clinical trials of the 6 most common noncutaneous solid cancers, published between January 1, 2012, and December 31, 2022, in 4 high-impact journals. Trial characteristics were recorded. The RQs for each race and ethnicity were calculated by dividing the percent of representation in each clinical trial publication by the percent of year-matched, site-specific incident cancers in the US, compared with Kruskal-Wallis tests with Bonferroni correction (BC). Reporting was compared between journal publications and ClinicalTrials.gov. Findings: Among 1202 publications evaluated, 364 met inclusion criteria: 16 JAMA, 241 Journal of Clinical Oncology, 19 Lancet, and 88 New England Journal of Medicine. Publications included 268 209 patients (171 132 women [64%]), with a median of 356 (IQR, 131-800) patients per publication. Reported race and ethnicity included American Indian or Alaska Native in 52 (14%) publications, Asian in 196 (54%), Black or African American in 215 (59%), Hispanic in 67 (18%), Native Hawaiian or Other Pacific Islander in 28 (8%), and White in 254 (70%). Median RQ varied across race (P < .001 BC), with 1.04 (IQR, 0.09-4.77) for Asian, 0.98 (IQR, 0.86-1.06) for White, 0.42 (IQR, 0.12-0.75) for Black or African American, and 0.00 (IQR, 0.00-0.00) for both American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander patients. Sensitivity analyses showed similar findings on subset analysis for US-only clinical trials. There was significantly less race and ethnicity reporting in the clinical trial publications compared with ClinicalTrials.gov documentation for American Indian or Alaska Native (14% vs 45%; P < .001 per McNemar χ2 test with continuity correction [MC]) and Native Hawaiian or Other Pacific Islander (8% vs 43%; P < .001 MC). Conclusions and Relevance: While most phase 2/3 oncology clinical trials published in high-impact journals report race and ethnicity, most did not report American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander racial categories. Our findings support a call to action for consistent journal policies and transparent race and ethnicity reporting, in alignment with Affordable Care Act-concordant race and ethnicity federal reporting requirements.

Confidence intervals for odds ratio from multistage randomized phase II trials.

A multi-stage randomized trial design can significantly improve efficiency by allowing early termination of the trial when the experimental arm exhibits either low or high efficacy compared to the control arm during the study. However, proper inference methods are necessary because the underlying distribution of the target statistic changes due to the multi-stage structure. This article focuses on multi-stage randomized phase II trials with a dichotomous outcome, such as treatment response, and proposes exact conditional confidence intervals for the odds ratio. The usual single-stage confidence intervals are invalid when used in multi-stage trials. To address this issue, we propose a linear ordering of all possible outcomes. This ordering is conditioned on the total number of responders in each stage and utilizes the exact conditional distribution function of the outcomes. This approach enables the estimation of an exact confidence interval accounting for the multi-stage designs.

Statistical considerations in model-based dose finding for binary responses under model uncertainty.

The statistical methodology for model-based dose finding under model uncertainty has attracted increasing attention in recent years. While the underlying principles are simple and easy to understand, developing and implementing an efficient approach for binary responses can be a formidable task in practice. Motivated by the statistical challenges encountered in a phase II dose finding study, we explore several key design and analysis issues related to the hybrid testing-modeling approaches for binary responses. The issues include candidate model selection and specifications, optimal design and efficient sample size allocations, and, notably, the methods for dose-response testing and estimation. Specifically, we consider a class of generalized linear models suited for the candidate set and establish D-optimal designs for these models. Additionally, we propose using permutation-based tests for dose-response testing to avoid asymptotic normality assumptions typically required for contrast-based tests. We perform trial simulations to enhance our understanding of these issues.

Risk of hypertension in erenumab-treated patients with migraine: Analyses of clinical trial and postmarketing data.

OBJECTIVE: To assess the risk of hypertension in patients with migraine who received erenumab in clinical trials and in the postmarketing setting. BACKGROUND: Erenumab is a monoclonal antibody for migraine prevention that targets the calcitonin gene-related peptide (CGRP) receptor. Hypertension is a theoretical risk for inhibitors of the CGRP pathway. Although no evidence of an association between erenumab treatment and hypertension was observed during the clinical development program, adverse events (AEs) of hypertension have been identified in the postmarketing setting. METHODS: Safety data from four phase 2 and phase 3 clinical trials were used to perform a pooled analysis of hypertension AEs in patients with migraine receiving erenumab. Postmarketing AEs of hypertension were identified from the Amgen Global Safety database from May 17, 2018, through January 31, 2020. RESULTS: In the pooled analysis of clinical trials, hypertension AEs (placebo, 9/1043 [0.9%]; erenumab 70 mg, 7/893 [0.8%]; erenumab 140 mg, 1/507 [0.2%]) and percentage of patients initiating medication to treat hypertension (12/1043 [1.2%], 7/893 [0.8%], 1/507 [0.2%], respectively) were similar across treatment groups. A total of 362 AEs of hypertension were identified from the postmarketing setting, 26.2% (95/362) of which were serious, >245,000 patient-years of exposure. The exposure-adjusted incidence of hypertension was 0.144 per 100 patient-years. CONCLUSIONS: Clinical trials did not demonstrate an increased risk of hypertension with erenumab compared with placebo, and AE rates of hypertension reported with erenumab in the postmarketing setting were generally low. Additional data are needed to fully characterize the extent to which hypertension is a risk associated with erenumab.

The quality of clinical trials in neuroendocrine tumours; have we learnt from our mistakes? An evaluation of phase II and phase III clinical trials.

The quality and reporting of neuroendocrine tumour (NET) clinical trials has previously been found to be heterogeneous impairing trial interpretability. We aimed to perform an updated review of the quality of phase II/III clinical trials in NET to assess if trial design and reporting have improved since 2011. We performed a PubMed search for phase II/III trials evaluating systemic anticancer therapies or liver-directed therapies published between 2011 and 2018. Data collected comprised administrative data, study population characteristics, endpoints, reporting and statistical design parameters, and results. Sixty studies were included (5218 patients): 50 phase II and 10 phase III trials. Study populations were heterogeneous: 52% of trials allowed tumours from various primary sites, 28% allowed both well- and poorly-differentiated tumour morphology or did not specify, and 57% did not report proliferative indices and/or tumour grade in ≥80% of the study population. Only 36% of trials mandated radiological disease progression on participant enrolment using a validated measure. Statistical design and primary endpoint were clearly defined in 67% and 88% of trials, respectively. Toxicity (88%), radiological response rate (85%) and progression-free survival/time to progression (82%) were well reported in a majority of trials, but health-related quality of life was included in the minority. Of the randomised trials (n = 11), study populations were more homogeneous and study design was more often clearly defined; however, only 45% mandated radiological progression at baseline as measured per Response Evaluation Criteria In Solid Tumours, and reporting of health-related quality of life (55%) remained suboptimal. The design and reporting of NET clinical trials, predominantly of single-arm phase II trials, remains suboptimal and has not considerably improved over time despite the growth in our knowledge of the biology and unique characteristics of NETs. Higher quality is seen in randomised trials, although certain design and reporting elements remain inadequate in some studies. We must prioritise the design and conduct of NET clinical trials to effectively inform future research and guide practice change.

Improved survival with enasidenib versus standard of care in relapsed/refractory acute myeloid leukemia associated with IDH2 mutations using historical data and propensity score matching analysis.

BACKGROUND: The present study evaluated the relative survival benefits associated with enasidenib and current standard of care (SoC) therapies for patients with relapsed/refractory (R/R) acute myeloid leukemia (AML) and an isocitrate dehydrogenase 2 (IDH2) mutation who are ineligible for hematopoietic stem cell transplantation (HSCT). METHODS: Propensity score matching (PSM) analysis compared survival outcomes observed with enasidenib 100 mg daily in the phase I/II AG221-C-001 trial and SoC outcomes obtained from a real-world chart review of patients in France. RESULTS: Before matching, enasidenib (n = 195) was associated with numerically improved overall survival (OS) relative to SoC (n = 80; hazard ratio [HR], 0.82; 95% confidence interval [CI], 0.61-1.11). After matching and adjusting for covariates (n = 78 per group), mortality risk was significantly lower with enasidenib than with SoC (HR, 0.67; 95% CI, 0.47-0.97). The median OS was 9.26 months for enasidenib (95% CI, 7.72-13.24) and 4.76 months for SoC (95% CI, 3.81-8.21). Results remained robust across all sensitivity analyses conducted. CONCLUSIONS: PSM analyses indicate that enasidenib significantly prolongs survival relative to SoC among patients with R/R AML and an IDH2 mutation who are ineligible for HSCT. Future prospective studies are needed to validate these findings using other data sources and to assess the comparative efficacy of enasidenib for other treatment outcomes.

Impact of pre-treatment C-reactive protein level and skeletal muscle mass on outcomes after stereotactic body radiotherapy for T1N0M0 non-small cell lung cancer: a supplementary analysis of the Japan Clinical Oncology Group study JCOG0403.

This study aimed to evaluate the impact of pretreatment C-reactive protein (CRP) and skeletal muscle mass (SMM) on outcomes after stereotactic body radiotherapy (SBRT) for T1N0M0 non-small cell lung cancer (NSCLC) as a supplementary analysis of JCOG0403. Patients were divided into high and low CRP groups with a threshold value of 0.3 mg/dL. The paraspinous musculature area at the level of the 12th thoracic vertebra was measured on simulation computed tomography (CT). When the area was lower than the sex-specific median, the patient was classified into the low SMM group. Toxicities, overall survival (OS) and cumulative incidence of cause-specific death were compared between the groups. Sixty operable and 92 inoperable patients were included. In the operable cohort, OS significantly differed between the CRP groups (log-rank test p = 0.009; 58.8% and 83.6% at three years for high and low CRP, respectively). This difference in OS was mainly attributed to the difference in lung cancer deaths (Gray's test p = 0.070; 29.4% and 7.1% at three years, respectively). No impact of SMM on OS was observed. The incidence of Grade 3-4 toxicities tended to be higher in the low SMM group (16.7% vs 0%, Fisher's exact test p = 0.052). In the inoperable cohort, no significant impact on OS was observed for either CRP or SMM. The toxicity incidence was also not different between the CRP and SMM groups. The present study suggests that pretreatment CRP level may provide prognostic information in operable patients receiving SBRT for early-stage NSCLC.

Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials.

Clinical trial efficiency, defined as facilitating patient enrollment, and reducing the time to reach safety and efficacy decision points, is a critical driving factor for making improvements in therapeutic development. The present work evaluated a machine learning (ML) approach to improve phase II or proof-of-concept trials designed to address unmet medical needs in treating schizophrenia. Diagnostic data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) trial were used to develop a binary classification ML model predicting individual patient response as either "improvement," defined as greater than 20% reduction in total Positive and Negative Syndrome Scale (PANSS) score, or "no improvement," defined as an inadequate treatment response (<20% reduction in total PANSS). A random forest algorithm performed best relative to other tree-based approaches in model ability to classify patients after 6 months of treatment. Although model ability to identify true positives, a measure of model sensitivity, was poor (<0.2), its specificity, true negative rate, was high (0.948). A second model, adapted from the first, was subsequently applied as a proof-of-concept for the ML approach to supplement trial enrollment by identifying patients not expected to improve based on their baseline diagnostic scores. In three virtual trials applying this screening approach, the percentage of patients predicted to improve ranged from 46% to 48%, consistently approximately double the CATIE response rate of 22%. These results show the promising application of ML to improve clinical trial efficiency and, as such, ML models merit further consideration and development.

Fragility index of trials supporting approval of anti-cancer drugs in common solid tumours.

BACKGROUND: The Fragility Indexquantifies the reliability of positive trials by estimating the number of events, which would change statistically significant results to non-significant results. METHODS: We identified randomized trials supporting drug approvals by the US FDA between 2009 and 2019 in lung, breast, prostate, and colon cancers and in melanoma. We reconstructed survival tablesand calculated the number of events, which would result in a non-significant result for the primary endpoint. The FI was then compared to the number of patients in each trial who withdrew consent or were lost to follow-up. Regression analyses were used to explore associations between RCT characteristics and FI and trials in which FI was lower or equal to number of participants who withdrew consent or were lost to follow-up. RESULTS: Among 81 RCTs, the median FI was 28. The median number of patients who withdrew consent or were lost to follow up was 27. FI was equal or lower than the number of patients who withdrew consent or were lost to follow-up in 47 trials (58%). There was a modest increase in FI over time (p = 0.02). Trials with overall survival as the primary endpoint (p = 0.006) and those in the palliative setting (p < 0.001) had lower FI. There was no association with trial sample size or duration of follow-up. FINDINGS: Statistical significance of RCTs in common solid tumours can be reversed often with a small number of additional events. Post-approval RCTs or real-world data analyses should be performed to ensure results of registration trials are robust.

Daratumumab in multiple myeloma: experience of the multiple myeloma GIMEMA Lazio group.

Daratumumab (DARA) is a human IgG-K monoclonal antibody (MoAb) targeting CD38 that is approved alone or in combination with bortezomib and dexamethasone or lenalidomide and dexamethasone for relapsed or refractory MM (RRMM) in patients previously exposed or double refractory to proteasome inhibitors (PI) and immunomodulatory drugs (IMiDs). However, there are limited data on its clinical activity and tolerability in real-world patients. Therefore, in the present study, we aim to determine the efficacy and toxicity profile of daratumumab in a real-life setting. In this study, we report the experience of the multiple myeloma GIMEMA Lazio Group in 62 relapsed/refractory MM patients treated with daratumumab as monotherapy who had previously received at least two treatment lines including a PI and an IMiDs or had been double refractory. Patients received DARA 16 mg/kg intravenously weekly for 8 weeks, every 2 weeks for 16 weeks, and every 4 weeks until disease progression or unacceptable toxicity. The overall response rate to daratumumab was 46%. Median progression-free survival (PFS) and overall survival reached 2.7 and 22.4 months, respectively. DARA was generally well tolerated; however, 2 patients interrupted their therapy due to adverse events. Present real-life experience confirms that DARA monotherapy is an effective strategy for heavily pre-treated and refractory patients with multiple myeloma, with a favorable safety profile.

Systematic review of phase-I/II trials enrolling refractory and recurrent Ewing sarcoma: Actual knowledge and future directions to optimize the research.

BACKGROUND: Optimal Phase-II design to evaluate new therapies in refractory/relapsed Ewing sarcomas (ES) remains imperfectly defined. OBJECTIVES: Recurrent/refractory ES phase-I/II trials analysis to improve trials design. METHODS: Comprehensive review of therapeutic trials registered on five databases (who.int/trialsearch, clinicaltrials.gov, clinicaltrialsregister.eu, e-cancer.fr, and umin.ac.jp) and/or published in PubMed/ASCO/ESMO websites, between 2005 and 2018, using the criterion: (Ewing sarcoma OR bone sarcoma OR sarcoma) AND (Phase-I or Phase-II). RESULTS: The 146 trials identified (77 phase-I/II, 67 phase-II, and 2 phase-II/III) tested targeted (34%), chemo- (23%), immune therapies (19%), or combined therapies (24%). Twenty-three trials were ES specific and 48 had a specific ES stratum. Usually multicentric (88%), few trials were international (30%). Inclusion criteria cover the recurrent ES age range for only 12% of trials and allowed only accrual of measurable diseases (RECIST criteria). Single-arm design was the most frequent (88%) testing mainly single drugs (61%), only 5% were randomized. Primary efficacy outcome was response rate (RR=CR+PR; Complete+Partial response) (n = 116/146; 79%), rarely progression-free or overall survival (16% PFS and 3% OS). H0 and H1 hypotheses were variable (3%-25% and 20%-50%, respectively). The 62 published trials enrolled 827 ES patients. RR was poor (10%; 15 CR=1.7%, 68 PR=8.3%). Stable disease was the best response for 186 patients (25%). Median PFS/OS was of 1.9 (range 1.3-14.7) and 7.6 months (5-30), respectively. Eleven (18%) published trials were considered positive, with median RR/PFS/OS of 15% (7%-30%), 4.5 (1.3-10), and 16.6 months (6.9-30), respectively. CONCLUSION: This review supports the need to develop the international randomized phase-II trials across all age ranges with PFS as primary endpoint.

A personalized approach to guide allogeneic stem cell transplantation in younger adults with acute myeloid leukemia.

A multistage model instructed by a large dataset (knowledge bank [KB] algorithm) has recently been developed to improve outcome predictions and tailor therapeutic decisions, including hematopoietic stem cell transplantation (HSCT) in acute myeloid leukemia (AML). We assessed the performance of the KB in guiding HSCT decisions in first complete remission (CR1) in 656 AML patients younger than 60 years from the ALFA-0702 trial (NCT00932412). KB predictions of overall survival (OS) were superior to those of European LeukemiaNet (ELN) 2017 risk stratification (C-index, 68.9 vs 63.0). Among patients reaching CR1, HSCT in CR1, as a time-dependent covariate, was detrimental in those with favorable ELN 2017 risk and those with negative NPM1 minimal residual disease (MRD; interaction tests, P = .01 and P = .02, respectively). Using KB simulations of survival at 5 years in a scenario without HSCT in CR1 (KB score), we identified, in a similar time-dependent analysis, a significant interaction between KB score and HSCT, with HSCT in CR1 being detrimental only in patients with a good prognosis based on KB simulations (KB score ≥40; interaction test, P = .01). We could finally integrate ELN 2017, NPM1 MRD, and KB scores to sort 545 CR1 patients into 278 (51.0%) HSCT candidates and 267 (49.0%) chemotherapy-only candidates. In both time-dependent and 6-month landmark analyses, HSCT significantly improved OS in HSCT candidates, whereas it significantly shortened OS in chemotherapy-only candidates. Integrating KB predictions with ELN 2017 and MRD may thus represent a promising approach to optimize HSCT timing in younger AML patients.

Analysis of Patient-Reported Outcome Utilization Within National Clinical Trials Network Cooperative Group Radiation Oncology Trials Over the Past 2 Decades.

PURPOSE: When treating cancer, both quantity and quality of life are valuable, though oncology trials have long placed greater emphasis on the former. The goal of this work was to evaluate how patient-reported outcomes (PROs) have been incorporated into radiation therapy trials within the National Clinical Trials Network over the last 2 decades to measure quality of life and to assess how PRO data have been disseminated in publications upon trial conclusion. METHODS AND MATERIALS: This cross-sectional study analyzed the frequency of use of PROs in National Clinical Trials Network cooperative group radiation therapy phase 2 and 3 clinical trials over the past 2 decades. A literature review was performed to determine the publication outcomes of PRO data, including only trials that used PROs in their design and were mature enough to have published results. RESULTS: Fifty-seven (56.4%) of the 101 trials included in this study included PROs in their design. Brain and head and neck trials demonstrated the largest proportional incorporation of PROs (81.8% and 76.9%, respectively), and thoracic and breast trials used the fewest (18.8% and 37.5%, respectively). The EQ-5D family of questionnaires was the most commonly used PROs, used in 22.8% of trials included. The literature review demonstrated a pattern of increased publication of PRO data alongside survival endpoints in manuscripts derived from these trials over time. CONCLUSIONS: Though there is room for improvement, the field of radiation oncology has embraced the incorporation of PROs into multicenter, high-impact clinical trials over the past 2 decades and has increased its publication of this data alongside survival data from these trials.

Age-dependent increase of treatment-related mortality in older patients with aggressive B cell lymphoma: analysis of outcome, treatment feasibility, and toxicity in 1171 elderly patients with aggressive B cell lymphoma-data from phase II and III trials of the DSHNHL (German High-Grade Non-Hodgkin's Lymphoma Study Group).

In elderly patients (pts) with aggressive B cell lymphoma (aNHL), curative treatment often cannot be administered because of comorbidities and tolerability. We analyzed the influence of age in pts > 60 years receiving the R-CHOP-14 regimen within different prospective DSHNHL trials. Of the RICOVER-60 trial and CHOP-R-ESC trials, 1171 aNHL pts were included in this retrospective analysis of age-dependent event-free survival (EFS), progression-free survival (PFS), and overall survival (OS). All patients received prophylactic G-CSF, and anti-infective prophylaxis with amphotericin B mouth wash and oral fluorchinolone was optional. In the CHOP-R-ESC trials, prophylaxis was augmented to include mandatory continuous orally administered aciclovir and a pneumocystis prophylaxis with cotrimoxazole as well as oral fluorchinolones during neutropenia. The patient population was separated into 4 age groups (61-65 years, 66-70 years, 71-75 years, and 76-80 years). The results from the RICOVER-60 trial were subsequently confirmed in the following CHOP-R-ESC trials by a multivariate analysis adjusted for IPI factors and gender. Significant differences (p < 0.001) in EFS, PFS, and OS were seen between age groups (RICOVER-60). Hematotoxicity, infections, and TRM increased with age. TRM was significantly elevated in the age group 76-80 years. Therefore, this analysis shows that an age above 75 years defines an especially vulnerable patient population when being treated with chemoimmunotherapy for aNHL. Prophylactic anti-infective drugs are essential and clinically effective in reducing morbidity when treating elderly aNHL pts.

Venetoclax with decitabine vs intensive chemotherapy in acute myeloid leukemia: A propensity score matched analysis stratified by risk of treatment-related mortality.

Hypomethylating agents (HMA) with venetoclax is a new standard for older/unfit patients with acute myeloid leukemia (AML). However, it is unknown how HMA with venetoclax compare to intensive chemotherapy (IC) in patients who are "fit" or "unfit" for IC. We compared outcomes of older patients with newly diagnosed AML receiving 10-day decitabine with venetoclax (DEC10-VEN) vs IC. DEC10-VEN consisted of daily venetoclax with decitabine 20 mg/m2 for 10 days for induction and decitabine for 5 days as consolidation. The IC cohort received regimens containing cytarabine ≥1 g/m2 /d. A validated treatment-related mortality score (TRMS) was used to classify patients at high-risk or low-risk for TRM with IC. Propensity scores were used to match patients to minimize bias. Median age of the DEC10-VEN cohort (n = 85) was 72 years (range 63-89) and 28% patients were at high-risk of TRM with IC. The comparator IC group (n = 85) matched closely in terms of baseline characteristics. DEC10-VEN was associated with significantly higher CR/CRi compared to IC (81% vs 52%, P < .001), and lower rate of relapse (34% vs 56%, P = .01), 30-day mortality (1% vs 24%, P < .01), and longer overall survival (OS; 12.4 vs 4.5 months, HR = 0.48, 95%CI 0.29-0.79, P < .01). In patients at both at high-risk and low-risk of TRM, DEC10-VEN showed significantly higher CR/CRi, lower 30-day mortality, and longer OS compared to IC. Patients at both high-risk and low-risk of TRM had comparable outcomes with DEC10-VEN. In conclusion, DEC10-VEN offers better outcomes compared to intensive chemotherapy in older patients with newly diagnosed AML, particularly in those at high-risk of TRM.

Local Investigators Significantly Overestimate Overall Response Rates Compared to Blinded Independent Central Reviews in Phase 2 Oncology Trials.

The overall response rate (ORR) is a largely adopted outcome measure in early-phase oncology trials. ORR is highly relevant in cancer drug development at the time of deciding whether to move to confirmatory phase 3 trials; moreover, ORR is gaining increasing relevance in fast-track registration procedures. No systematic analysis has been conducted so far to investigate whether a discrepancy exists between ORR assessed by local investigators and those assessed by blinded reviewers in phase 2 oncology trials. In this study, we carried out a search in the clinicaltrials.gov and EudraCT databases, looking at the trials reporting the results of both investigator-assessed and independently-assessed ORR. A discrepancy index was obtained by calculating the ratio of each investigator-assessed ORR on the corresponding independently assessed ORR, so that a discrepancy index >1 indicates that the investigator was "more optimistic," whereas a discrepancy index <1 indicates the opposite. We also analyzed different subgroups (by tumor type, by drug type, by year). Twenty trials met the search criteria; in some cases, >1 comparison was conducted in the trial, so that the total number of comparisons analyzed was 33. The estimated mean discrepancy index was 1.175 (95% confidence interval, 1.083-1.264; n = 33). In conclusion, local investigators significantly overestimate ORR compared to paired blinded reviewers in phase 2 oncology trials. This may represent a risk in drug development, when deciding whether to move to confirmatory, more expensive phase 3 trials. Blinded independent central review should be used in ORR assessment if a more conservative estimate of treatment efficacy is required, as in the case of fast-track drug developments leading to accelerated approvals of cancer therapies.