Design of Phase II cancer trials evaluating survival probabilities

Data-driven monitoring for phase II clinical trial designs based on percentile event time test

The goal of phase II clinical trials is to evaluate the therapeutic efficacy of a new drug. Some investigators want to use the time-to-event endpoint as the primary endpoint of the phase II study to see the improvement of the therapeutic efficacy of a new drug in median survival time. Recently, median event time test (METT) has been proposed to provide a simple and straightforward rule which compares the observed median survival time with the prespecified threshold. However, median survival time would not be observed during the trial if the drug performs well and indeed cures most patients or if the accrual rate is so fast. To address the issues in clinical practice, we first propose a percentile event time test (PETT), which generalizes METT to any percentile of the survival time, and develop data-driven monitoring for phase II clinical trial designs based on PETT. We evaluate the performance of the method through simulations and illustrate the proposed method with a trial example.

Sample size determination and evaluation for two-stage adaptive designs of single arm clinical trials based on median event time test

Clinical trials play a critical role in drug development which involves a series of phases and requires a significant amount of time and effort. Efficient clinical trial designs are necessary to investigate a new drug. Investigators strongly desire to use the time-to-event endpoint as the primary endpoint for Phase II studies, which evaluates the therapeutic efficacy of the new drug, with the hypothesis that the new drug improves the median survival time. The one-sample log-rank test has been used for single-arm Phase II trials, but it generally requires more samples. Recently, the median event time test was proposed to provide a simple, straightforward decision rule, which compares the observed median survival time for the new drug with the threshold, which is determined through the numerical search. We improve the computation of the method for the two-stage design of single-arm clinical trials based on the median event time test. By utilizing the large sample theory of order statistics, we provide the explicit formulas to calculate the sample size for the first and second stages and propose the testing procedure. The performance of the proposed method is evaluated through simulations and a trial example.

Romidepsin-CHOEP followed by high-dose chemotherapy and stem-cell transplantation in untreated Peripheral T-Cell Lymphoma: results of the PTCL13 phase Ib/II study

The standard treatment for young patients with untreated PTCLs is based on anthracycline containing-regimens followed by high-dose-chemotherapy and stem-cell-transplantation (HDT + SCT), but only 40% of them can be cured. Romidepsin, a histone-deacetylase inhibitor, showed promising activity in relapsed PTCLs; in first line, Romidepsin was added with CHOP. We designed a study combining romidepsin and CHOEP as induction before HDT + auto-SCT in untreated PTCLs (PTCL-NOS, AITL/THF, ALK-ALCL), aged 18-65 years. A phase Ib/II trial was conducted to define the maximum tolerated dose (MTD) of Ro-CHOEP, and to assess efficacy and safety of 6 Ro-CHOEP as induction before HDT. The study hypothesis was to achieve a 18-month PFS of 70%. Twenty-one patients were enrolled into phase Ib; 7 dose-limiting toxicities were observed, that led to define the MTD at 14 mg/ms. Eighty-six patients were included in the phase II. At a median follow-up of 28 months, the 18-month PFS was 46.2% (95%CI:35.0-56.7), and the 18-month overall survival was 73.1% (95%CI:61.6-81.7). The overall response after induction was 71%, with 62% CRs. No unexpected toxicities were reported. The primary endpoint was not met; therefore, the enrollment was stopped at a planned interim analysis. The addition of romidepsin to CHOEP did not improve the PFS of untreated PTCL patients.

Bayesian single-arm phase II trial designs with time-to-event endpoints

For the cancer clinical trials with immunotherapy and molecularly targeted therapy, time-to-event endpoint is often a desired endpoint. In this paper, we present an event-driven approach for Bayesian one-stage and two-stage single-arm phase II trial designs. Two versions of Bayesian one-stage designs were proposed with executable algorithms and meanwhile, we also develop theoretical relationships between the frequentist and Bayesian designs. These findings help investigators who want to design a trial using Bayesian approach have an explicit understanding of how the frequentist properties can be achieved. Moreover, the proposed Bayesian designs using the exact posterior distributions accommodate the single-arm phase II trials with small sample sizes. We also proposed an optimal two-stage approach, which can be regarded as an extension of Simon's two-stage design with the time-to-event endpoint. Comprehensive simulations were conducted to explore the frequentist properties of the proposed Bayesian designs and an R package BayesDesign can be assessed via R CRAN for convenient use of the proposed methods.

Optimal two-stage design of single arm Phase II clinical trials based on median event time test

The Phase II clinical trials aim to assess the therapeutic efficacy of a new drug. The therapeutic efficacy has been often quantified by response rate such as overall response rate or survival probability in the Phase II setting. However, there is a strong desire to use survival time, which is the gold standard endpoint for the confirmatory Phase III study, when investigators set the primary objective of the Phase II study and test hypotheses based on the median survivals. We propose a method for median event time test to provide the sample size calculation and decision rule of testing. The decision rule is simple and straightforward in that it compares the observed median event time to the identified threshold. Moreover, it is extended to optimal two-stage design for practice, which extends the idea of Simon’s optimal two-stage design for survival endpoint. We investigate the performance of the proposed methods through simulation studies. The proposed methods are applied to redesign a trial based on median event time for trial illustration, and practical strategies are given for application of proposed methods.

Two-stage optimal designs based on exact variance for a single-arm trial with survival endpoints

Sample size calculation based on normal approximations is often associated with the loss of statistical power for a single-arm trial with a time-to-event endpoint. Recently, Wu (2015) derived the exact variance for the one-sample log-rank test under the alternative and showed that a single-arm one-stage study based on exact variance often has power above the nominal level while the type I error rate is controlled. We extend this approach to a single-arm two-stage design by using exact variances of the one-sample log-rank test for the first stage and the two stages combined. The empirical power of the proposed two-stage optimal designs is often not guaranteed under a two-stage design setting, which could be due to the asymptotic bi-variate normal distribution used to estimate the joint distribution of the test statistics. We adjust the nominal power level in the design search to guarantee the simulated power of the identified optimal design being above the nominal level. The sample size and the study time savings of the proposed two-stage designs are substantial as compared to the one-stage design.

Two-stage phase II survival trial design

Recently, molecularly targeted agents and immunotherapy have been advanced for the treatment of relapse or refractory cancer patients, where disease progression-free survival or event-free survival is often a primary endpoint for the trial design. However, methods to evaluate two-stage single-arm phase II trials with a time-to-event endpoint are currently processed under an exponential distribution, which limits application of real trial designs. In this paper, we developed an optimal two-stage design, which is applied to the four commonly used parametric survival distributions. The proposed method has advantages compared with existing methods in that the choice of underlying survival model is more flexible and the power of the study is more adequately addressed. Therefore, the proposed two-stage design can be routinely used for single-arm phase II trial designs with a time-to-event endpoint as a complement to the commonly used Simon's two-stage design for the binary outcome.

Investigating the potential clinical benefit of Selumetinib in resensitising advanced iodine refractory differentiated thyroid cancer to radioiodine therapy (SEL-I-METRY): protocol for a multicentre UK single arm phase II trial

BACKGROUND

Thyroid cancer is the most common endocrine malignancy. Some advanced disease is, or becomes, resistant to radioactive iodine therapy (refractory disease); this holds poor prognosis of 10% 10-year overall survival. Whilst Sorafenib and Lenvatinib are now licenced for the treatment of progressive iodine refractory thyroid cancer, these treatments require continuing treatment and can be associated with significant toxicity. Evidence from a pilot study has demonstrated feasibility of Selumetinib to allow the reintroduction of I-131 therapy; this larger, multicentre study is required to demonstrate the broader clinical impact of this approach before progression to a confirmatory trial.

METHODS

SEL-I-METRY is a UK, single-arm, multi-centre, two-stage phase II trial. Participants with locally advanced or metastatic differentiated thyroid cancer with at least one measureable lesion and iodine refractory disease will be recruited from eight NHS Hospitals and treated with four-weeks of oral Selumetinib and assessed for sufficient I-123 uptake (defined as any uptake in a lesion with no previous uptake or 30% or greater increase in uptake). Those with sufficient uptake will be treated with I-131 and followed for clinical outcomes. Radiation absorbed doses will be predicted from I-123 SPECT/CT and verified from scans following the therapy. Sixty patients will be recruited to assess the primary objective of whether the treatment schedule leads to increased progression-free survival compared to historical control data.

DISCUSSION

The SEL-I-METRY trial will investigate the effect of Selumetinib followed by I-131 therapy on progression-free survival in radioiodine refractory patients with differentiated thyroid cancer showing increased radioiodine uptake following initial treatment with Selumetinib. In addition, information on toxicity and dosimetry will be collected. This study presents an unprecedented opportunity to investigate the role of lesional dosimetry in molecular radiotherapy, leading to greater personalisation of therapy. To date this has been a neglected area of research. The findings of this trial will be useful to healthcare professionals and patients alike to determine whether further study of this agent is warranted. It is hoped that the development of the infrastructure to deliver a multicentre trial involving molecular radiotherapy dosimetry will lead to further trials in this field.

TRIAL REGISTRATION

SEL-I-METRY is registered under ISRCTN17468602 , 02/12/2015.

Two-stage optimal designs with survival endpoint when the follow-up time is restricted

BACKGROUND

Survival endpoint is frequently used in early phase clinical trials as the primary endpoint to assess the activity of a new treatment. Existing two-stage optimal designs with survival endpoint either over estimate the sample size or compute power outside the alternative hypothesis space.

METHODS

We propose a new single-arm two-stage optimal design with survival endpoint by using the one-sample log rank test based on exact variance estimates. This proposed design with survival endpoint is analogous to Simon's two-stage design with binary endpoint, having restricted follow-up.

RESULTS

We compare the proposed design with the existing two-stage designs, including the two-stage design with survival endpoint based on the nonparametric Nelson-Aalen estimate, and Simon's two-stage designs with or without interim accrual. The new design always performs better than these competitors with regards to the expected total study length, and requires a smaller expected sample size than Simon's design with interim accrual.

CONCLUSIONS

The proposed two-stage minimax and optimal designs with survival endpoint are recommended for use in practice to shorten the study length of clinical trials.

Phase I/IIa study of concomitant radiotherapy with olaparib and temozolomide in unresectable or partially resectable glioblastoma: OLA-TMZ-RTE-01 trial protocol

BACKGROUND

Despite multimodality treatments including neurosurgery, radiotherapy and chemotherapy, glioblastoma (GBM) prognosis remains poor. GBM is classically considered as a radioresistant tumor, because of its high local recurrence rate, inside the irradiation field. The development of new radiosensitizer is crucial to improve the patient outcomes. Pre-clinical data showed that Poly (ADP-ribose) polymerase inhibitors (PARPi) could be considered as a promising class of radiosensitizer. The aim of this study is to evaluate Olaparib, a PARPi, as radiosensitizing agent, combined with the Stupp protocol, namely temozolomide (TMZ) and intensity modulated radiotherapy (IMRT) in first line treatment of partially or non-resected GBM.

METHODS

The OLA-TMZ-RTE-01 study is a multicenter non-randomized phase I/IIa trial including unresectable or partially resectable GBM patients, from 18 to 70 years old. A two-step dose-escalation phase I design will first determine the recommended phase 2 dose (RP2D) of olaparib, delivered concomitantly with TMZ plus conventional irradiation for 6 weeks and as single agent for 4 weeks (radiotherapy period), and second, the RP2D of olaparib combined with adjuvant TMZ (maintenance period). Phase IIa will assess the 18-month overall survival (OS) of this combination. In both phase I and IIa separately considered, the progression-free survival, the objective response rate, the neurocognitive functions of patients, emotional disorders among caregivers, the survival without toxicity, degradation nor progression, the complications onset and the morphologic and functional MRI (magnetic resonance imaging) parameters will be also assessed as secondary objectives. Ancillary objectives will explore alteration of the DNA repair pathways on biopsy tumor, proton magnetic resonance spectroscopy parameters to differentiate tumor relapse and radionecrosis, and an expanded cognition evaluation. Up to 79 patients will be enrolled: 30 patients in the phase I and 49 patients in the phase IIa.

DISCUSSION

Combining PARP inhibitors, such as olaparib, with radiotherapy and chemotherapy in GBM may improve survival outcomes, while sparing healthy tissue and preserving neurocognitive function, given the replication-dependent efficacy of olaparib, and the increased PARP expression in GBM as compared to non-neoplastic brain tissue. Ancillary studies will help to identify genetic biomarkers predictive of PARPi efficacy as radiosensitizer.

TRIAL REGISTRATION

NCT03212742 , registered June, 7, 2017. Protocol version: Version 2.2 dated from 2017/08/18.

CRITICS-II: a multicentre randomised phase II trial of neo-adjuvant chemotherapy followed by surgery versus neo-adjuvant chemotherapy and subsequent chemoradiotherapy followed by surgery versus neo-adjuvant chemoradiotherapy followed by surgery in resectable gastric cancer

Background

Although radical surgery remains the cornerstone of cure in resectable gastric cancer, survival remains poor. Current evidence-based (neo)adjuvant strategies have shown to improve outcome, including perioperative chemotherapy, postoperative chemoradiotherapy and postoperative chemotherapy. However, these regimens suffer from poor patient compliance, particularly in the postoperative phase of treatment. The CRITICS-II trial aims to optimize preoperative treatment by comparing three treatment regimens: (1) chemotherapy, (2) chemotherapy followed by chemoradiotherapy and (3) chemoradiotherapy.

Methods

In this multicentre phase II non-comparative study, patients with clinical stage IB-IIIC (TNM 8th edition) resectable gastric adenocarcinoma are randomised between: (1) 4 cycles of docetaxel+oxaliplatin+capecitabine (DOC), (2) 2 cycles of DOC followed by chemoradiotherapy (45Gy in combination with weekly paclitaxel and carboplatin) or (3) chemoradiotherapy. Primary endpoint is event-free survival, 1 year after randomisation (events are local and/or regional recurrence or progression, distant recurrence, or death from any cause). Secondary endpoints include: toxicity, surgical outcomes, percentage radical (R0) resections, pathological tumour response, disease recurrence, overall survival, and health related quality of life. Exploratory endpoints include translational studies on predictive and prognostic biomarkers.

Discussion

The aim of this study is to select the most promising among three preoperative treatment arms in patients with resectable gastric adenocarcinoma. This treatment regimen will subsequently be compared with the standard therapy in a phase III trial.

Trial registration

clinicaltrials.gov NCT02931890; registered 13 October 2016. Date of first enrolment: 21 December 2017.

A two-stage design for phase II trials with time-to-event endpoint using restricted follow-up

In phase II oncology trials, the use of new cytostatic drugs raises some questions regarding the endpoint. Time-to-event endpoints such as Progression-Free Survival have been recommended and led to new designs. In 2003, Case and Morgan proposed a design based on the comparison of the cumulative hazards at a clinically relevant timepoint. In 2013, Kwak proposed a design based on the one-sample log-rank test. If all the patients are followed from their entry time to the analysis date, the Kwak and Jung's design leads to a smaller sample size as compared to the Case-Morgan's design. However, the Case and Morgan's design requires less information since it only needs to follow every patient during a fixed interval of time. We propose a trade-off between these two approaches that corresponds to an adaptation of Kwak and Jung's design when the follow-up is expected to be restricted. Our proposal is based on the one-sample log-rank test as the Kwak and Jung's design but it uses the same follow-up information as the Case-Morgan's design. Simulation study shows that our proposal allows reducing the sample size as compared to the Case-Morgan's design (median difference of 23% [15%-33%]). Type I and type II error rates are close to their nominal rates planned in the protocol. A real phase II clinical trial in cervical cancer illustrated the interest of this new design. Thus, our proposal can be recommended as an alternative to the Kwak's design when patients' follow-up is restricted.

Some statistical considerations in the clinical development of cancer immunotherapies

Immuno-oncology has emerged as an exciting new approach to cancer treatment. Common immunotherapy approaches include cancer vaccine, effector cell therapy, and T-cell-stimulating antibody. Checkpoint inhibitors such as cytotoxic T lymphocyte-associated antigen 4 and programmed death-1/L1 antagonists have shown promising results in multiple indications in solid tumors and hematology. However, the mechanisms of action of these novel drugs pose unique statistical challenges in the accurate evaluation of clinical safety and efficacy, including late-onset toxicity, dose optimization, evaluation of combination agents, pseudoprogression, and delayed and lasting clinical activity. Traditional statistical methods may not be the most accurate or efficient. It is highly desirable to develop the most suitable statistical methodologies and tools to efficiently investigate cancer immunotherapies. In this paper, we summarize these issues and discuss alternative methods to meet the challenges in the clinical development of these novel agents. For safety evaluation and dose-finding trials, we recommend the use of a time-to-event model-based design to handle late toxicities, a simple 3-step procedure for dose optimization, and flexible rule-based or model-based designs for combination agents. For efficacy evaluation, we discuss alternative endpoints/designs/tests including the time-specific probability endpoint, the restricted mean survival time, the generalized pairwise comparison method, the immune-related response criteria, and the weighted log-rank or weighted Kaplan-Meier test. The benefits and limitations of these methods are discussed, and some recommendations are provided for applied researchers to implement these methods in clinical practice.

Single-arm Phase II cancer survival trial designs

The current practice for designing single-arm Phase II trials with time-to-event endpoints is limited to using either a maximum likelihood estimate test under the exponential model or a naive approach based on dichotomizing the event time at a landmark time point. A trial designed under the exponential model may not be reliable, and the naive approach is inefficient. The modified one-sample log-rank test statistic proposed in this article fills the void. In general, the proposed test can be used to design single-arm Phase II survival trials under any parametric survival distribution. Simulation results showed that it preserves type I error well and provides adequate power for Phase II cancer trial designs with time-to-event endpoints.

Mixed response and time-to-event endpoints for multistage single-arm phase II design

BACKGROUND

The objective of phase II cancer clinical trials is to determine if a treatment has sufficient activity to warrant further study. The efficiency of a conventional phase II trial design has been the object of considerable debate, particularly when the study regimen is characteristically cytostatic. At the time of development of a phase II cancer trial, we accumulated clinical experience regarding the time to progression (TTP) for similar classes of drugs and for standard therapy. By considering the time to event (TTE) in addition to the tumor response endpoint, a mixed-endpoint phase II design may increase the efficiency and ability of selecting promising cytotoxic and cytostatic agents for further development.

METHODS

We proposed a single-arm phase II trial design by extending the Zee multinomial method to fully use mixed endpoints with tumor response and the TTE. In this design, the dependence between the probability of response and the TTE outcome is modeled through a Gaussian copula.

RESULTS

Given the type I and type II errors and the hypothesis as defined by the response rate (RR) and median TTE, such as median TTP, the decision rules for a two-stage phase II trial design can be generated. We demonstrated through simulation that the proposed design has a smaller expected sample size and higher early stopping probability under the null hypothesis than designs based on a single-response endpoint or a single TTE endpoint.

CONCLUSIONS

The proposed design is more efficient for screening new cytotoxic or cytostatic agents and less likely to miss an effective agent than the alternative single-arm design.

Bayesian methods for setting sample sizes and choosing allocation ratios in phase II clinical trials with time-to-event endpoints

Conventional phase II trials using binary endpoints as early indicators of a time-to-event outcome are not always feasible. Uveal melanoma has no reliable intermediate marker of efficacy. In pancreatic cancer and viral clearance, the time to the event of interest is short, making an early indicator unnecessary. In the latter application, Weibull models have been used to analyse corresponding time-to-event data. Bayesian sample size calculations are presented for single-arm and randomised phase II trials assuming proportional hazards models for time-to-event endpoints. Special consideration is given to the case where survival times follow the Weibull distribution. The proposed methods are demonstrated through an illustrative trial based on uveal melanoma patient data. A procedure for prior specification based on knowledge or predictions of survival patterns is described. This enables investigation into the choice of allocation ratio in the randomised setting to assess whether a control arm is indeed required. The Bayesian framework enables sample sizes consistent with those used in practice to be obtained. When a confirmatory phase III trial will follow if suitable evidence of efficacy is identified, Bayesian approaches are less controversial than for definitive trials. In the randomised setting, a compromise for obtaining feasible sample sizes is a loss in certainty in the specified hypotheses: the Bayesian counterpart of power. However, this approach may still be preferable to running a single-arm trial where no data is collected on the control treatment. This dilemma is present in most phase II trials, where resources are not sufficient to conduct a definitive trial.

Challenges of clinical trial design for targeted agents against pediatric leukemias

The past 40 years have seen significant improvements in both event-free and overall survival for children with acute lymphoblastic and acute myeloid leukemia (ALL and AML, respectively). Serial national and international clinical trials have optimized the use of conventional chemotherapeutic drugs and, along with improvements in supportive care that have enabled the delivery of more intensive regimens, have been responsible for the major improvements in patient outcome seen over the past few decades. However, the benefits of dose intensification have likely now been maximized, and over the same period, the identification of new cytotoxic drugs has been limited. Therefore, challenges remain if survival is to be improved further. In pediatric ALL, 5-year-survival rates of over 85% have been achieved with risk-stratified therapy, but a notable minority of patients will still not be cured. In pediatric AML, different challenges remain. A slower improvement in overall survival has taken place in this patient population. Despite the obvious morphological heterogeneity of AML blasts, biological stratification is comparatively limited, and translation into risk-stratified therapeutic approaches has only best characterized by the use of retinoic acid for t(15;17)-positive AML. Even where prognostic markers have been identified, limited therapeutic options or multi-drug resistance of AML blasts has limited the impact on patient benefit. For both, the acute morbidities of current treatment remain significant and may be life-threatening alone. In addition, the Childhood Cancer Survivor Study (CCSS) highlighted many leukemia survivors develop one or more chronic medical conditions attributable to treatment (1, 2). As the biology of leukemogenesis has become better understood, key molecules and intracellular pathways have been identified that offer the possibility of targeting directly the leukemia cells while sparing normal cells. Consequently, there is now a drive to develop novel leukemia-specific or "targeted" therapies. These new classes of drugs will have mechanisms of action, toxicities, and therapeutic indices quite different from conventional cytotoxic drugs previously encountered, thus rendering current clinical trial methodologies inappropriate. Clinical trial methods will need to be adapted to accommodate these features of these new classes of drugs. This review will address the challenges and some of the techniques for developing clinical trials for targeted therapies.

Single-Arm Phase II Group Sequential Trial Design with Survival Endpoint at a Fixed Time Point

In this paper, three non-parametric test statistics are proposed to design single-arm phase II group sequential trials for monitoring survival probability. The small-sample properties of these test statistics are studied through simulations. Sample size formulas are derived for the fixed sample test. The Brownian motion property of the test statistics allowed us to develop a flexible group sequential design using a sequential conditional probability ratio test procedure (Xiong, 1995). An example is given to illustrate the trial design by using the proposed method.

Figitumumab in patients with refractory metastatic colorectal cancer previously treated with standard therapies: a nonrandomized, open-label, phase II trial

PURPOSE

Figitumumab (CP-751,871) is a human IgG2 monoclonal antibody that binds and down-regulates insulin-like growth factor receptor-1 (IGF-1R) and inhibits activation of this receptor by IGF-1 and IGF-2. This nonrandomized, open-label, single-arm, phase II trial evaluated the antitumor activity and safety of figitumumab in patients with metastatic colorectal cancer that was refractory to ≥2 systemic therapies.

METHODS

Cohorts A and B received intravenous figitumumab 20 and 30 mg/kg in 3-week cycles, respectively. Both received loading doses (20 or 30 mg/kg) on days 1 and 2 of cycle 1. The primary endpoint was 6-month survival (null hypothesis for each cohort, H0: p6 mo surv = 0.45). Secondary endpoints included progression-free survival (PFS), overall survival (OS), objective response, safety, and pharmacokinetics.

RESULTS

A total of 168 patients (Cohort A, n = 85; Cohort B, n = 83) received figitumumab. Estimated 6-month survival was 49.4 % (95 % CI 38.8-60.0) in Cohort A and 44.1 % (95 % CI 33.4-54.9) in Cohort B. Median OS was 5.8 and 5.6 months, respectively; median PFS was 1.4 months in both cohorts. No objective partial or complete responses occurred. The respective rates of treatment discontinuation due to treatment-related adverse events (AEs) were 5 and 7 %. The most common grade 3/4 nonhematologic AEs in both cohorts were hyperglycemia and asthenia. No grade 4 hematologic laboratory abnormalities occurred. Most deaths were reported as due to progressive disease; none were due to figitumumab.

CONCLUSION

Six-month survival data do not support further study of figitumumab 20 or 30 mg/kg in this patient population.

Diffuse intrinsic pontine glioma treated with prolonged temozolomide and radiotherapy--results of a United Kingdom phase II trial (CNS 2007 04)

Diffuse intrinsic pontine glioma (DIPG) has a dismal prognosis with no chemotherapy regimen so far resulting in any significant improvement over standard radiotherapy. In this trial, a prolonged regimen (21/28d) of temozolomide was studied with the aim of overcoming O(6)-methylguanine methyltransferase (MGMT) mediated resistance. Forty-three patients with a defined clinico-radiological diagnosis of DIPG received radiotherapy and concomitant temozolomide (75 mg/m(2)) after which up to 12 courses of 21d of adjuvant temozolomide (75-100mg/m(2)) were given 4 weekly. The trial used a 2-stage design and passed interim analysis. At diagnosis median age was 8 years (2-20 years), 81% had cranial nerve abnormalities, 76% ataxia and 57% long tract signs. Median Karnofsky/Lansky score was 80 (10-100). Patients received a median of three courses of adjuvant temozolomide, five received all 12 courses and seven did not start adjuvant treatment. Three patients were withdrawn from study treatment due to haematological toxicity and 10 had a dose reduction. No other significant toxicity related to temozolomide was noted. Overall survival (OS) (95% confidence interval (CI)) was 56% (40%, 69%) at 9 months, 35% (21%, 49%) at 1 year and 17% (7%, 30%) at 2 years. Median survival was 9.5 months (range 7.5-11.4 months). There were five 2-year survivors with a median age of 13.6 years at diagnosis. This trial demonstrated no survival benefit of the addition of dose dense temozolomide, to standard radiotherapy in children with classical DIPG. However, a subgroup of adolescent DIPG patients did have a prolonged survival, which needs further exploration.

Screened selection design for randomised phase II oncology trials: an example in chronic lymphocytic leukaemia

BACKGROUND

As there are limited patients for chronic lymphocytic leukaemia trials, it is important that statistical methodologies in Phase II efficiently select regimens for subsequent evaluation in larger-scale Phase III trials.

METHODS

We propose the screened selection design (SSD), which is a practical multi-stage, randomised Phase II design for two experimental arms. Activity is first evaluated by applying Simon's two-stage design (1989) on each arm. If both are active, the play-the-winner selection strategy proposed by Simon, Wittes and Ellenberg (SWE) (1985) is applied to select the superior arm. A variant of the design, Modified SSD, also allows the arm with the higher response rates to be recommended only if its activity rate is greater by a clinically-relevant value. The operating characteristics are explored via a simulation study and compared to a Bayesian Selection approach.

RESULTS

Simulations showed that with the proposed SSD, it is possible to retain the sample size as required in SWE and obtain similar probabilities of selecting the correct superior arm of at least 90%; with the additional attractive benefit of reducing the probability of selecting ineffective arms. This approach is comparable to a Bayesian Selection Strategy. The Modified SSD performs substantially better than the other designs in selecting neither arm if the underlying rates for both arms are desirable but equivalent, allowing for other factors to be considered in the decision making process. Though its probability of correctly selecting a superior arm might be reduced, it still performs reasonably well. It also reduces the probability of selecting an inferior arm.

CONCLUSIONS

SSD provides an easy to implement randomised Phase II design that selects the most promising treatment that has shown sufficient evidence of activity, with available R codes to evaluate its operating characteristics.

Bayesian decision theoretic two-stage design in phase II clinical trials with survival endpoint

In this paper, we consider two-stage designs with failure-time endpoints in single-arm phase II trials. We propose designs in which stopping rules are constructed by comparing the Bayes risk of stopping at stage I with the expected Bayes risk of continuing to stage II using both the observed data in stage I and the predicted survival data in stage II. Terminal decision rules are constructed by comparing the posterior expected loss of a rejection decision versus an acceptance decision. Simple threshold loss functions are applied to time-to-event data modeled either parametrically or nonparametrically, and the cost parameters in the loss structure are calibrated to obtain desired type I error and power. We ran simulation studies to evaluate design properties including types I and II errors, probability of early stopping, expected sample size, and expected trial duration and compared them with the Simon two-stage designs and a design, which is an extension of the Simon's designs with time-to-event endpoints. An example based on a recently conducted phase II sarcoma trial illustrates the method.

Designing Phase II B trials in sarcopenia: the best target population

Despite the existing limitations and controversies regarding the definition of sarcopenia and its clinical consequences, the current scientific evidence strongly suggests that muscle decline is a primary determinant of the disabling process (and likely of other major health-related events). In fact, the muscle loss (in terms of mass as well as strength) occurring with aging has been growingly associated with mobility impairment and disability in older persons. Unfortunately, current evidence is mainly from observational studies. Times are mature to begin testing interventions aimed at modifying the sarcopenia process through the design and development of specific clinical trials. Considering the emergence of many promising interventions towards this age-related condition (e.g., physical exercise [in particular, resistance training], testosterone, antioxidant supplementations), the need for Phase II trial designs is high. In the present report, we discuss which are the major issues related to the design of Phase II clinical trials on sarcopenia with particular focus on the participant's characteristics to be considered as possible inclusion and exclusion criteria.

Phase II Clinical Trials in Oncology: Strengths and Limitations of Two-Stage Designs

Two-stage designs are used widely in Phase II oncology clinical trials to reduce the number of patients placed on ineffective experimental therapies. They provide clear-cut rules for stopping early in the event that treatment is not succeeding as hoped and are relatively simple to implement. Such designs, however, can lead to situations in which patient accrual is continued in the face of a clearly inferior treatment. In situations where patients' response can be determined for many or most subjects before additional patients are enrolled, analyses using Bayesian methodology can lead to earlier termination of studies of ineffective treatments and better align the statistical assessment of treatment effect with the therapeutic objectives of study. These points are discussed in context of the role of Phase II clinical trials in the development of new treatments for cancer.

A two-stage phase II trial design utilizing both primary and secondary endpoints

Phase II trials in oncology drug development are usually conducted to perform the initial assessment of treatment activity. The common designs in this setting, for example, Simon 2-stage designs, are often developed based on testing whether a parameter of interest, usually a proportion (e.g. response rate), is less than a certain level or not. These designs usually consider only one parameter. However, sometimes we may encounter situations where we need to consider not a single parameter, but multiple parameters. This paper presents a two-stage design in which both primary and secondary endpoints are utilized in the decision rules. The family-wise Type 1 error rate and statistical power of the proposed design are investigated under a variety of situations by means of Monte-Carlo simulations.