A benchmark for dose-finding studies with unknown ordering.

An important tool to evaluate the performance of a dose-finding design is the nonparametric optimal benchmark that provides an upper bound on the performance of a design under a given scenario. A fundamental assumption of the benchmark is that the investigator can arrange doses in a monotonically increasing toxicity order. While the benchmark can be still applied to combination studies in which not all dose combinations can be ordered, it does not account for the uncertainty in the ordering. In this article, we propose a generalization of the benchmark that accounts for this uncertainty and, as a result, provides a sharper upper bound on the performance. The benchmark assesses how probable the occurrence of each ordering is, given the complete information about each patient. The proposed approach can be applied to trials with an arbitrary number of endpoints with discrete or continuous distributions. We illustrate the utility of the benchmark using recently proposed dose-finding designs for Phase I combination trials with a binary toxicity endpoint and Phase I/II combination trials with binary toxicity and continuous efficacy.

Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial.

PURPOSE: Cytology and cystoscopy, the current gold standard for diagnosing urothelial carcinomas, have limits: cytology has high interobserver variability with moderate or not optimal sensitivity (particularly for low-grade tumors); while cystoscopy is expensive, invasive, and operator dependent. The VISIOCYT1 study assessed the benefit of VisioCyt® for diagnosing urothelial carcinoma. METHODS: VISIOCYT1 was a French prospective clinical trial conducted in 14 centers. The trial enrolled adults undergoing endoscopy for suspected bladder cancer or to explore the lower urinary tract. Participants were allocated either Group 1: with bladder cancer, i.e., with positive cystoscopy or with negative cystoscopy but positive cytology, or Group 2: without bladder cancer. Before cystoscopy and histopathology, slides were prepared for cytology and the VisioCyt® test from urine samples. The diagnostic performance of VisioCyt® was assessed using sensitivity (primary objective, 70% lower-bound threshold) and specificity (75% lower-bound threshold). Sensitivity was also assessed by tumor grade and T-staging. VisioCyt® and cytology performance were evaluated relative to the histopathological assessments. RESULTS: Between October 2017 and December 2019, 391 participants (170 in Group 1 and 149 in Group 2) were enrolled. VisioCyt®'s sensitivity was 80.9% (95% CI 73.9-86.4%) and specificity was 61.8% (95% CI 53.4-69.5%). In high-grade tumors, the sensitivity was 93.7% (95% CI 86.0-97.3%) and in low-grade tumors 66.7% (95% CI 55.2-76.5%). Sensitivity by T-staging, compared to the overall sensitivity, was higher in high-grade tumors and lower in low-grade tumors. CONCLUSION: VisioCyt® is a promising diagnostic tool for urothelial cancers with improved sensitivities for high-grade tumors and notably for low-grade tumors.

Multilayer spectrum of intratumoral heterogeneity in basal bladder cancer.

Basal/squamous (Ba/Sq) subtype represents an intrinsic and robust group in the consensus molecular classification of muscle-invasive bladder cancer (MIBC), with poor outcome and controversial chemosensitivity. We aimed to investigate the spectrum of intratumor heterogeneity (ITH) in the Ba/Sq subtype. First, we validated a 29-gene NanoString CodeSet to predict the Ba/Sq subtype for FFPE samples. We identified heterogeneous Ba/Sq tumors in a series of 331 MIBC FFPE samples using dual GATA3/KRT5/6 immunohistochemistry (IHC). Heterogeneous regions with distinct immunostaining patterns were studied separately for gene expression using the 29-gene CodeSet, for mutations by targeted next-generation sequencing, and for copy number alteration (CNA) by microarray hybridization. Among 83 Ba/Sq tumors identified by GATA3/KRT5/6 dual staining, 19 tumors showed heterogeneity at the IHC level. In one third of the 19 cases, regions from the same tumor were classified in different distinct molecular subtypes. The mutational and CNA profiles confirmed the same clonal origin for IHC heterogeneous regions with possible subclonal evolution. Overall, two patterns of intratumoral heterogeneity (ITH) were observed in Ba/Sq tumors: low ITH (regions with distinct immunostaining, but common molecular subtype and shared CNA) or high ITH (regions with distinct immunostaining, molecular subtype, and CNA). These results showed multilayer heterogeneity in Ba/Sq MIBC. In view of personalized medicine, this heterogeneity adds complexity and should be taken into account for sampling procedures used for diagnosis and treatment choice. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Survival after sentinel lymph node biopsy for early cervical cancers: a systematic review and meta-analysis.

BACKGROUND: Sentinel lymph node biopsy represents an alternative to pelvic lymphadenectomy for lymph node staging of early-stage cervical carcinoma, but prospective evidence on long-term oncological safety of sentinel lymph node biopsy alone versus pelvic lymphadenectomy is missing. OBJECTIVE: To investigate, with this meta-analysis, the impact of sentinel lymph node biopsy alone versus pelvic lymphadenectomy on survival for patients with early-stage cervical cancer. METHODS: A systematic literature review was performed. We excluded studies in which pelvic lymphadenectomy was systematically performed after every sentinel lymph node biopsy, including only articles where pelvic lymphadenectomy was performed because sentinel lymph node biopsy was not conclusive. A meta-analysis was carried out combining 5-year disease-free survival and overall survival rates with a random and fixed effect model. Heterogeneity was tested using the Cochran Χ2 test and quantified with Higgins information I2. RESULTS: The search of databases and registers found 927 items and six articles (two retrospective and four prospective). The median time of follow-up was 34.8 months (range 13-53). Overall common effect disease-free survival was 98% while random effect disease-free survival was 94%. Overall heterogeneity was 77%. A subgroup analysis was applied, dividing studies into one group including sentinel lymph node biopsy negative data only (common effect disease-free survival 91%; random effect disease-free survival 90%), and one group with a negative and positive sentinel lymph node biopsy (common effect disease-free survival 98%; random effect disease-free survival 96%). In the analysis of overall survival, positive and negative sentinel lymph node biopsy cases were examined together (common and random effect overall survival 99%). Ultrastaging did not affect disease-free survival (common and random effect disease-free survival 92% in the ultrastaging group vs common effect disease-free survival 99% and random effect disease-free survival 96% in the non-ultrastaging group). CONCLUSIONS: Both 5-year disease-free survival and overall survival rate after sentinel lymph node biopsy alone are higher than 90% and do not differ from pelvic lymphadenectomy survival data. Ultrastaging did not impact survival.

Clinical impact of low-volume lymph node metastases in early-stage cervical cancer: A comprehensive meta-analysis.

OBJECTIVE: In order to define the clinical significance of low-volume metastasis, a comprehensive meta-analysis of published data and individual data obtained from articles mentioning micrometastases (MIC) and isolated tumor cells (ITC) in cervical cancer was performed, with a follow up of at least 3 years. METHODS: We performed a systematic literature review and meta-analysis, following Cochrane's review methods guide and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The primary outcome was the disease-free survival (DFS), and the secondary outcome was the overall survival (OS). The hazard ratio (HR) was taken as the measure of the association between the low-volume metastases (MIC+ITC and MIC alone) and DFS or OS; it quantified the hazard of an event in the MIC (+/- ITC) group compared to the hazard in node-negative (N0) patients. A random-effect meta-analysis model using the inverse variance method was selected for pooling. Forest plots were used to display the HRs and risk differences within individual trials and overall. RESULTS: Eleven articles were finally retained for the meta-analysis. In the analysis of DFS in patients with low-volume metastasis (MIC + ITC), the HR was increased to 2.60 (1.55-4.34) in the case of low-volume metastasis vs. N0. The presence of MICs had a negative prognostic impact, with an HR of 4.10 (2.71-6.20) compared to N0. Moreover, this impact was worse than that of MIC pooled with ITCs. Concerning OS, the meta-analysis shows an HR of 5.65 (2.81-11.39) in the case of low-volume metastases vs. N0. The presence of MICs alone had a negative effect, with an HR of 6.94 (2.56-18.81). CONCLUSIONS: In conclusion, the presence of MIC seems to be associated with a negative impact on both the DFS and OS and should be treated as MAC.

The International Collaboration for Research methods Development in Oncology (CReDO) workshops: shaping the future of global oncology research.

Low-income and middle-income countries (LMICs) have a disproportionately high burden of cancer and cancer mortality. The unique barriers to optimum cancer care in these regions necessitate context-specific research. The conduct of research in LMICs has several challenges, not least of which is a paucity of formal training in research methods. Building capacity by training early career researchers is essential to improve research output and cancer outcomes in LMICs. The International Collaboration for Research methods Development in Oncology (CReDO) workshop is an initiative by the Tata Memorial Centre and the National Cancer Grid of India to address gaps in research training and increase capacity in oncology research. Since 2015, there have been five CReDO workshops, which have trained more than 250 oncologists from India and other countries in clinical research methods and protocol development. Participants from all oncology and allied fields were represented at these workshops. Protocols developed included clinical trials, comparative effectiveness studies, health services research, and observational studies, and many of these protocols were particularly relevant to cancer management in LMICs. A follow-up of these participants in 2020 elicited an 88% response rate and showed that 42% of participants had made progress with their CReDO protocols, and 73% had initiated other research protocols and published papers. In this Policy Review, we describe the challenges to research in LMICs, as well as the evolution, structure, and impact of CReDO and other similar workshops on global oncology research.

A benchmark for dose finding studies with continuous outcomes.

An important tool to evaluate the performance of any design is an optimal benchmark proposed by O'Quigley and others (2002. Non-parametric optimal design in dose finding studies. Biostatistics3, 51-56) that provides an upper bound on the performance of a design under a given scenario. The original benchmark can only be applied to dose finding studies with a binary endpoint. However, there is a growing interest in dose finding studies involving continuous outcomes, but no benchmark for such studies has been developed. We show that the original benchmark and its extension by Cheung (2014. Simple benchmark for complex dose finding studies. Biometrics70, 389-397), when looked at from a different perspective, can be generalized to various settings with several discrete and continuous outcomes. We illustrate and compare the benchmark's performance in the setting of a dose finding Phase I clinical trial with a continuous toxicity endpoint and a Phase I/II trial with binary toxicity and continuous efficacy endpoints. We show that the proposed benchmark provides an accurate upper bound in these contexts and serves as a powerful tool for evaluating designs.

Incorporating patient centered benefits as endpoints in randomized trials of maintenance therapies in advanced ovarian cancer: A position paper from the GCIG symptom benefit committee.

BACKGROUND: Quality of life and patient reported outcome measures (PROMs) are important secondary endpoints and incorporated in most contemporary clinical trials. There have been deficiencies in their assessment and reporting in ovarian cancer clinical trials, particularly in trials of maintenance treatment where they are of particular importance. The Gynecologic Cancer InterGroup (GCIG) symptom benefit committee (SBC) recently convened a brainstorming meeting with representation from all collaborative groups to address questions of how to best incorporate PROMs into trials of maintenance therapies to support the primary endpoint which is usually progression free survival (PFS). These recommendations should harmonize the collection, analysis and reporting of PROM's across future GCIG trials. METHODS: Through literature review, trials analysis and input from international experts, the SBC identified four relevant topics to address with respect to promoting the role of PROMs to support the PFS endpoint in clinical trials of maintenance treatment for OC. RESULTS: The GCIG SBC unanimously accepted the importance of integrating PROM's in future maintenance trials and developed four guiding principles to be considered early in trial design. These include 1) adherence to SPIRIT-PRO guidelines, 2) harmonization of selection, collection and reporting of PROM's; 3) combining Health Related Quality of Life (HRQL) measures with clinical endpoints and 4) common approaches to dealing with incomplete HRQL data. CONCLUSIONS: Close attention to incorporating HRQL and PROM's is critical to interpret the results of ovarian cancer clinical trials of maintenance therapies. There should be a consistent approach to assessing and reporting patient centered benefits across all GCIG trials to enable cross trial comparisons which can be used to inform practice.

Change-point joint model for identification of plateau of activity in early phase trials.

This article presents a phase I/II trial design for targeted therapies and immunotherapies, with the objective of identifying the optimal dose (OD). We employ a joint modeling technique for discrete time-to-event toxicity data and repeated and continuous biomarker measurements. For the biomarker measurements, we implement a change point linear mixed effects skeleton model. This model can accommodate both plateauing and nonplateauing dose-activity relationships. For each new cohort of patients, we estimate the maximum tolerated dose (MTD) taking toxicity as a cumulative endpoint, over six treatment cycles. Then, we select the OD using two different criteria. The OD is a dose that is equally active to the MTD or a dose located on the beginning of the plateau of the dose-activity relationship. Joint modeling allows us to take into account informative censoring due to toxicities or lack of activity and we also consider consent withdrawal and intermittent missing responses. Model estimation relies on likelihood inference.

Apalutamide, darolutamide and enzalutamide in nonmetastatic castration-resistant prostate cancer: a meta-analysis.

Aim: Comparison of the efficacy/safety/health-related quality of life of apalutamide, enzalutamide and darolutamide in Phase III clinical trials involving patients with nonmetastatic castration-resistant prostate cancer was performed. Materials & methods: Relevant studies were identified by searching PubMed as well as conference abstracts reporting updated overall survival. Three pivotal trials were identified, SPARTAN (apalutamide), PROSPER (enzalutamide) and ARAMIS (darolutamide), and form the basis of this analysis. Results: All three drugs significantly prolonged metastasis-free survival, prostate-specific antigen response and overall survival versus placebo, and were generally well tolerated. Conclusion: Drug selection will likely be influenced by tolerability/safety and other factors, such as the propensity for drug-drug interactions and the presence of comorbidities, that affect the risk-benefit balance in individual patients.

COVID-19 in breast cancer patients: a cohort at the Institut Curie hospitals in the Paris area.

BACKGROUND: Cancer patients have been reported to be at higher risk of COVID-19 complications and deaths. We report the characteristics and outcome of patients diagnosed with COVID-19 during breast cancer treatment at Institut Curie hospitals (ICH, Paris area, France). METHODS: An IRB-approved prospective registry was set up at ICH on March 13, 2020, for all breast cancer patients with COVID-19 symptoms or radiologic signs. Registered data included patient history, tumor characteristics and treatments, COVID-19 symptoms, radiological features, and outcome. Data extraction was done on April 25, 2020. COVID-19 patients were defined as those with either a positive RNA test or typical, newly appeared lung CT scan abnormalities. RESULTS: Among 15,600 patients actively treated for early or metastatic breast cancer during the last 4 months at ICH, 76 patients with suspected COVID-19 infection were included in the registry and followed. Fifty-nine of these patients were diagnosed with COVID-19 based on viral RNA testing (N = 41) or typical radiologic signs: 37/59 (63%) COVID-19 patients were treated for metastatic breast cancer, and 13/59 (22%) of them were taking corticosteroids daily. Common clinical features mostly consisted of fever and/or cough, while ground-glass opacities were the most common radiologic sign at diagnosis. We found no association between prior radiation therapy fields or extent of radiation therapy sequelae and extent of COVID-19 lung lesions. Twenty-eight of these 59 patients (47%) were hospitalized, and 6 (10%) were transferred to an intensive care unit. At the time of analysis, 45/59 (76%) patients were recovering or had been cured, 10/59 (17%) were still followed, and 4/59 (7%) had died from COVID-19. All 4 patients who died had significant non-cancer comorbidities. In univariate analysis, hypertension and age (> 70) were the two factors associated with a higher risk of intensive care unit admission and/or death. CONCLUSIONS: This prospective registry analysis suggests that the COVID-19 mortality rate in breast cancer patients depends more on comorbidities than prior radiation therapy or current anti-cancer treatment. Special attention must be paid to comorbidities when estimating the risk of severe COVID-19 in breast cancer patients.

Atezolizumab in combination with bevacizumab and chemotherapy versus bevacizumab and chemotherapy in recurrent ovarian cancer - a randomized phase III trial (AGO-OVAR 2.29/ENGOT-ov34).

BACKGROUND: Improvement in clinical outcomes of patients with platinum-resistant disease is an unmet medical need and trials in this population are urgently needed. Checkpoint-inhibitors have already shown activity in multiple other tumor entities and ovarian cancer, especially in the combination with anti-angiogenic treatment. PRIMARY OBJECTIVE: To test if the activity of non-platinum-based chemotherapy and bevacizumab could be improved by the addition of atezolizumab. STUDY HYPOTHESIS: The addition of atezolizumab to standard non-platinum combination of chemotherapy and bevacizumab improves median overall survival from 15 to 20 months. TRIAL DESIGN: Patients are randomized to chemotherapy (paclitaxel weekly or pegylated liposomal doxorubicin) + bevacizumab + placebo vs chemotherapy + bevacizumab + atezolizumab. Stratification factors are: number of prior lines, planned type of chemotherapy, prior use of bevacizumab, and tumor programmed death-ligand 1 (PD-L1) status. MAJOR INCLUSION/EXCLUSION CRITERIA: Recurrent epithelial ovarian, fallopian tube, or primary peritoneal cancer with up to three prior therapies and a treatment-free interval after platinum of less than 6 months. Patients with three prior lines of chemotherapy are eligible irrespective of the platinum free-interval. A de novo tumor tissue sample biopsy for determination of PD-L1 status prior to randomization for stratification is mandatory. Major exclusion criteria consider bevacizumab-specific and immunotherapy-specific criteria. PRIMARY ENDPOINT: Overall survival and progression-free survival are co-primary endpoints. SAMPLE SIZE: It is planned to randomize 664 patients. TRIAL REGISTRATION: NCT03353831.

A comparison of phase I dose-finding designs in clinical trials with monotonicity assumption violation.

BACKGROUND/AIMS: In oncology, new combined treatments make it difficult to order dose levels according to monotonically increasing toxicity. New flexible dose-finding designs that take into account uncertainty in dose levels ordering were compared with classical designs through simulations in the setting of the monotonicity assumption violation. We give recommendations for the choice of dose-finding design. METHODS: Motivated by a clinical trial for patients with high-risk neuroblastoma, we considered designs that require a monotonicity assumption, the Bayesian Continual Reassessment Method, the modified Toxicity Probability Interval, the Bayesian Optimal Interval design, and designs that relax monotonicity assumption, the Bayesian Partial Ordering Continual Reassessment Method and the No Monotonicity Assumption design. We considered 15 scenarios including monotonic and non-monotonic dose-toxicity relationships among six dose levels. RESULTS: The No Monotonicity Assumption and Partial Ordering Continual Reassessment Method designs were robust to the violation of the monotonicity assumption. Under non-monotonic scenarios, the No Monotonicity Assumption design selected the correct dose level more often than alternative methods on average. Under the majority of monotonic scenarios, the Partial Ordering Continual Reassessment Method selected the correct dose level more often than the No Monotonicity Assumption design. Other designs were impacted by the violation of the monotonicity assumption with a proportion of correct selections below 20% in most scenarios. Under monotonic scenarios, the highest proportions of correct selections were achieved using the Continual Reassessment Method and the Bayesian Optimal Interval design (between 52.8% and 73.1%). The costs of relaxing the monotonicity assumption by the No Monotonicity Assumption design and Partial Ordering Continual Reassessment Method were decreases in the proportions of correct selections under monotonic scenarios ranging from 5.3% to 20.7% and from 1.4% to 16.1%, respectively, compared with the best performing design and were higher proportions of patients allocated to toxic dose levels during the trial. CONCLUSIONS: Innovative oncology treatments may no longer follow monotonic dose levels ordering which makes standard phase I methods fail. In such a setting, appropriate designs, as the No Monotonicity Assumption or Partial Ordering Continual Reassessment Method designs, should be used to safely determine recommended for phase II dose.

Using a dose-finding benchmark to quantify the loss incurred by dichotomization in Phase II dose-ranging studies.

While there is recognition that more informative clinical endpoints can support better decision-making in clinical trials, it remains a common practice to categorize endpoints originally measured on a continuous scale. The primary motivation for this categorization (and most commonly dichotomization) is the simplicity of the analysis. There is, however, a long argument that this simplicity can come at a high cost. Specifically, larger sample sizes are needed to achieve the same level of accuracy when using a dichotomized outcome instead of the original continuous endpoint. The degree of "loss of information" has been studied in the contexts of parallel-group designs and two-stage Phase II trials. Limited attention, however, has been given to the quantification of the associated losses in dose-ranging trials. In this work, we propose an approach to estimate the associated losses in Phase II dose-ranging trials that is free of the actual dose-ranging design used and depends on the clinical setting only. The approach uses the notion of a nonparametric optimal benchmark for dose-finding trials, an evaluation tool that facilitates the assessment of a dose-finding design by providing an upper bound on its performance under a given scenario in terms of the probability of the target dose selection. After demonstrating how the benchmark can be applied to Phase II dose-ranging trials, we use it to quantify the dichotomization losses. Using parameters from real clinical trials in various therapeutic areas, it is found that the ratio of sample sizes needed to obtain the same precision using continuous and binary (dichotomized) endpoints varies between 70% and 75% under the majority of scenarios but can drop to 50% in some cases.

Sequential or combined designs for Phase I/II clinical trials? A simulation study.

BACKGROUND: Phase I and Phase II clinical trials aim at identifying a dose that is safe and active. Both phases are increasingly combined. For Phase I/II trials, two main types of designs are debated: a dose-escalation stage to select the maximum tolerated dose, followed by an expansion cohort to investigate its activity (dose-escalation followed by an expansion cohort), or a joint modelling to identify the best trade-off between toxicity and activity (efficacy-toxicity). We explore this question in the context of a paediatric Phase I/II platform trial. METHODS: In series of simulations, we assessed the operating characteristics of dose-escalation followed by an expansion cohort (DE-EC) designs without and with reassessment of the maximum tolerated dose during the expansion cohort (DE-ECext) and of the efficacy-toxicity (EffTox) design. We investigated the probability to identify an active and tolerable agent, that is, the percentage of correct decision, for various dose-toxicity activity scenarios. RESULTS: For a large therapeutic index, the percentage of correct decision reached 96.0% for efficacy-toxicity versus 76.1% for dose-escalation followed by an expansion cohort versus 79.6% for DE-ECext. Conversely, when all doses were deemed not active, the percentage of correct decision was 47% versus 55.9% versus 69.2%, respectively, for efficacy-toxicity, dose-escalation followed by an expansion cohort and DE-ECext. Finally, in the case of a narrow therapeutic index, the percentage of correct decision was 48.0% versus 64.3% versus 67.2%, respectively, efficacy-toxicity, dose-escalation followed by an expansion cohort and DE-ECext. CONCLUSION: As narrow indexes are common in oncology, according to the present results, the sequential dose-escalation followed by an expansion cohort is recommended. The importance to re-estimate the maximum tolerated dose during the expansion cohort is confirmed. However, despite their theoretical advantages, Phase I/II designs are challenged by the variations in populations between the Phase I and the Phase II parts and by the lagtime in the evaluation of toxicity and activity.

Randomized dose-escalation designs for drug combination cancer trials with immunotherapy.

This work considers Phase I cancer dual-agent dose-escalation clinical trials in which one of the compounds is an immunotherapy. The distinguishing feature of trials considered is that the dose of one agent, referred to as a standard of care, is fixed and another agent is dose-escalated. Conventionally, the goal of a Phase I trial is to find the maximum tolerated combination (MTC). However, in trials involving an immunotherapy, it is also essential to test whether a difference in toxicities associated with the MTC and the standard of care alone is present. This information can give useful insights about the interaction of the compounds and can provide a quantification of the additional toxicity burden and therapeutic index. We show that both, testing for difference between toxicity risks and selecting MTC can be achieved using a Bayesian model-based dose-escalation design with two modifications. Firstly, the standard of care administrated alone is included in the trial as a control arm and each patient is randomized between the control arm and one of the combinations selected by a model-based design. Secondly, a flexible model is used to allow for toxicities at the MTC and the control arm to be modeled directly. We compare the performance of two-parameter and four-parameter logistic models with and without randomization to a current standard of such trials: a one-parameter model. It is found that at the cost of a small reduction in the proportion of correct selections in some scenarios, randomization provides a significant improvement in the ability to test for a difference in the toxicity risks. It also allows a better fitting of the combination-toxicity curve that leads to more reliable recommendations of the combination(s) to be studied in subsequent phases.

Time to progression ratio in cancer patients enrolled in early phase clinical trials: time for new guidelines?

BACKGROUND: Reliable evaluation of treatment benefit in early phase clinical trials is necessary. The time to progression ratio (TTPr), which compares successive TTP in a single patient, is a powerful criteria for determining targeted or immune therapies efficacy. METHODS: We evaluated 205 TTPr in a large cohort of 177 advanced cancer patients enrolled in at least two Phase 1/1b trials (out of 2827 phase 1/1b-treated patients) at Gustave Roussy. RESULTS: This first wide description of TTPr showed that, under the hypothesis of overall absence of treatment line effect, the median TTPr was 0.7 and that 25% of patients presented a TTPr above the conventional efficacy threshold of 1.3. CONCLUSIONS: A higher median TTPr and a larger proportion of patients above the 1.3 threshold should therefore be achieved to conclude to drug efficacy. New guidelines for TTPr interpretation and calibration are proposed, which warrant independent prospective validation.

Outcomes and prognostic factors for relapsed or refractory lymphoma patients in phase I clinical trials.

Background Although safety and prognostic factors for overall survival (OS) have been extensively studied in Phase I clinical trials on patients with solid tumours, data on lymphoma trials are scarce. Here, we investigated safety, outcomes and prognostic factors in relapsed or refractory lymphoma patients included in a series of Phase I trials. Method and patients All consecutive adult patients with recurrent/refractory lymphoma enrolled in 26 Phase I trials at a single cancer centre in France between January 2008 and June 2016 were retrospectively assessed. Results 133 patients (males: 65%) were included in the analysis. The median (range) age was 65 (23-86). Aggressive non-Hodgkin, indolent non-Hodgkin and Hodgkin types accounted for 64%, 25% and 11% of the patients, respectively. The patients had received a median (range) of 3 (1-13) lines of treatment prior to trial entry. The median [95% confidence interval] progression-free survival and OS times were 3.0 [1.8-3.6] and 17.8 [12.7-30.4] months, respectively. High-grade toxicity (grade 3 or higher, according to the National Cancer Institute's Common Terminology Criteria for Adverse Events classification) was experienced by 56 of the 133 patients (42%) and was related to the investigational drug in 44 of these cases (79%). No toxicity-related deaths occurred. Dose-limiting toxicity (DLT) was encountered in 11 (9%) of the 116 evaluable patients. High-grade toxicity occurred during the DLT period for 34 of the 56 patients (61%) and after the DLT period in the remaining 22 (39%). The main prognostic factors for poor OS were the histological type (i.e. tumour aggressiveness), an elevated serum LDH level, and a low serum albumin level. Early withdrawal from a trial was correlated with the performance status score, the histological type and the serum LDH level. The overall objective response and disease control rates were 24% and 57%, respectively. Conclusion Performance status, LDH, albumin and histological type (tumour aggressiveness) appear to be the most relevant prognostic factors for enrolling Phase I participants with relapsed or refractory lymphoma. 39% of the patients experienced a first high-grade toxic event after the dose-limiting toxicity period, suggesting that the conventional concept of dose-limiting toxicity (designed for chemotherapy) should be redefined in the era of modern cancer therapies.

Outcome of children with relapsed or refractory neuroblastoma: A meta-analysis of ITCC/SIOPEN European phase II clinical trials.

BACKGROUND: Few randomized trials have been conducted in children with relapsed/refractory neuroblastoma and data about outcomes including progression-free survival (PFS) in these patients are scarce. PROCEDURE: A meta-analysis of three phase II studies of children with relapsed/refractory neuroblastoma conducted in Europe (temozolomide, topotecan-vincristine-doxorubicin and topotecan-temozolomide) was performed. Individual patient data with extended follow-up were collected from the trial databases after publication to describe trial outcomes (response rate, clinical benefit ratio, duration of treatment, PFS, and overall survival [OS]). Characteristics of subjects with relapsed/refractory neuroblastoma were compared. RESULTS: Data from 71 children and adolescents with relapsed/refractory neuroblastoma were collected. Response definitions were not homogeneous in the three trials. Patients were on study for a median of 3.5 months (interquartile range [IQR] 1.9-6.2). Of those, 35.2% achieved a complete or partial response, 26.3% experienced a response after more than two cycles, and 23.9% received more than six cycles. Median PFS from study entry for all, refractory, and relapsed patients was 6.4 ± 1.0, 12.5 ± 6.8, and 5.7 ± 1.0 months, respectively (P = 0.006). Median OS from study entry for all, refractory, and relapsed patients was 16.1 ± 4.3, 27.9 ± 20.2, and 11.0 ± 1.6 months, respectively (P = 0.03). CONCLUSIONS: Baseline data for response rate, clinical benefit ratio, duration of treatment, PFS, and OS were provided. Two subpopulations (relapsed/refractory) were clearly distinct and should be included in the interpretation of all trials. These results should help informing the design of forthcoming studies in relapsed/refractory neuroblastoma.

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.