Experimental designs for phase I and phase I/II dose-finding studies

We review the rationale behind the statistical design of dose-finding studies as used in phase I and phase I/II clinical trials. We underline what the objectives of such dose-finding studies should be and why the widely used standard design fails to meet any of these objectives. The standard design is a ‘memoryless' design and we discuss how this impacts on practical behaviour. Designs introduced over the last two decades can be viewed as designs with memory and we discuss how these designs are superior to memoryless designs. By superior we mean that they require less patients overall, less patients to attain the maximum tolerated dose (MTD), and concentrate a higher percentage of patients at and near to the MTD. We reanalyse some recently published studies in order to provide support to our contention that markedly better results could have been achieved had a design with memory been used instead of a memoryless design

Controlled backfill in oncology dose-finding trials

The use of backfill in early phase dose-finding trials is a relatively recent practice. It consists of assigning patients to dose levels below the level where the study is at. The main reason for backfilling is to collect additional pharmacokinetic, pharmacodynamic and response data, in order to assess whether a plateau may exist on the dose-efficacy curve. This is a possibility in oncology with molecularly targeted agents or immunotherapy. Recommending for further study a dose level lower than the maximum tolerated dose could be supported in such situations. How to best allocate backfill patients to dose levels is not yet established. In this paper we propose to randomise backfill patients below the dose level where the study is at. A refinement of this would be to stop backfilling to lower dose levels when these show insufficient efficacy compared to higher levels, starting at dose level 1 and repeating this process sequentially. At study completion, data from all patients (both backfill patients and dose-finding patients) is used to estimate the dose-response curve. The fit from a change point model is compared to the fit of a monotonic model to identify a potential plateau. Using simulations, we show that this approach can identify the plateau on the dose-response curve when such a plateau exists, allowing the recommendation of a dose level lower than the maximum tolerated dose for future studies. This contribution provides a methodological framework for backfilling, from the perspective of both design and analysis in early phase oncology trials

Dose finding and O6-alkylguanine-DNA alkyltransferase study of cisplatin combined with temozolomide in paediatric solid malignancies

Cisplatin may have additive activity with temozolomide due to ablation of the DNA repair protein O6-alkylguanine-DNA alkyltransferase (MGMT). This phase I/II study determined recommended combination doses using the Continual Reassessment Method, toxicities and antitumour activity in paediatric patients, and evaluated MGMT in peripheral blood mononuclear cells (PBMCs) in order to correlate with haematological toxicity. In total, 39 patients with refractory or recurrent solid tumours (median age ∼13 years; 14 pretreated with high-dose chemotherapy, craniospinal irradiation, or having bone marrow involvement) were treated with cisplatin, followed the next day by oral temozolomide for 5 days every 4 weeks at dose levels 80 mg m−2/150 mg m−2 day−1, 80/200, and 100/200, respectively. A total of 38 patients receiving 113 cycles (median 2, range 1–7) were evaluable for toxicity. Dose-limiting toxicity was haematological in all but one case. Treatment-related toxicities were thrombocytopenia, neutropenia, nausea-vomiting, asthenia. Hearing loss was experienced in five patients with prior irradiation to the brain stem or posterior fossa. Partial responses were observed in two malignant glioma, one brain stem glioma, and two neuroblastoma. Median MGMT activity in PBMCs decreased after 5 days of temozolomide treatment: low MGMT activity correlated with increased severity of thrombocytopenia. Cisplatin–temozolomide combinations are well tolerated without additional toxicity to single-agent treatments; the recommended phase II dosage is 80 mg m−2 cisplatin and 150 mg m−2 × 5 temozolomide in heavily treated, and 200 mg m−2 × 5 temozolomide in less-heavily pretreated children

Dose Transition Pathways::The missing link between complex dose-finding designs and simple decision-making

The ever-increasing pace of development of novel therapies mandates efficient methodologies for assessment of their tolerability and activity. Evidence increasingly support the merits of model-based dose-finding designs in identifying the recommended phase II dose compared with conventional rule-based designs such as the 3 + 3 but despite this, their use remains limited. Here, we propose a useful tool, dose transition pathways (DTP), which helps overcome several commonly faced practical and methodologic challenges in the implementation of model-based designs. DTP projects in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, de-escalate, or stop early), using all the accumulated information. After specifying a model with favorable statistical properties, we utilize the DTP to fine-tune the model to tailor it to the trial's specific requirements that reflect important clinical judgments. In particular, it can help to determine how stringent the stopping rules should be if the investigated therapy is too toxic. Its use to design and implement a modified continual reassessment method is illustrated in an acute myeloid leukemia trial. DTP removes the fears of model-based designs as unknown, complex systems and can serve as a handbook, guiding decision-making for each dose update. In the illustrated trial, the seamless, clear transition for each dose recommendation aided the investigators' understanding of the design and facilitated decision-making to enable finer calibration of a tailored model. We advocate the use of the DTP as an integral procedure in the co-development and successful implementation of practical model-based designs by statisticians and investigators. Clin Cancer Res; 23(24); 7440-7. ©2017 AACR

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

Background: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures. Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies. Results: Methods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated. Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies

Development of a sensitive, low-cost and user-friendly centrifugal microfluidic cartridge for multi-analyte environmental monitoring

This paper describes the development of a simple centrifugal cartridge for the analysis of nitrite, ammonia and phosphate from a water sample. The cartridge is operated in combination with the Centrifugal Microfluidic Analysis System (CMAS)[1] which incorporates rotational control with optical and communication components for portable analysis of environmental and biomedical samples[1,2]. An LED and a photodiode allow colorimetric determination of specific analytes depending on which reagent-based analytical method is employed. Bluetooth wireless communications provides automatic uploading of analytical data to cloud-based information systems. Microfluidic discs consisting of three PMMA (Poly(methyl methacrylate)) layers bonded together by two PSA (Pressure Sensitive Adhesive) layers were prepared. The sample was transported from a single chamber to three aliquoting chambers at a low rotational frequency prior to the actuation of dissolvable film valves[3] at an increased rotational frequency to facilitate sample transport to reaction/detection chambers. Ammonia standards were analysed using a modified Berthelot method, the stannous chloride method was used to detect orthophosphate levels while a diazotization method was employed to determine nitrite concentration. Photodiode analysis on the CMAS platform obtained LOD’s of 0.233 ppm for ammonia and 0.189 ppm for orthophosphate and 50 ppb for nitrite

Adaptive design methods in clinical trials – a review

In recent years, the use of adaptive design methods in clinical research and development based on accrued data has become very popular due to its flexibility and efficiency. Based on adaptations applied, adaptive designs can be classified into three categories: prospective, concurrent (ad hoc), and retrospective adaptive designs. An adaptive design allows modifications made to trial and/or statistical procedures of ongoing clinical trials. However, it is a concern that the actual patient population after the adaptations could deviate from the originally target patient population and consequently the overall type I error (to erroneously claim efficacy for an infective drug) rate may not be controlled. In addition, major adaptations of trial and/or statistical procedures of on-going trials may result in a totally different trial that is unable to address the scientific/medical questions the trial intends to answer. In this article, several commonly considered adaptive designs in clinical trials are reviewed. Impacts of ad hoc adaptations (protocol amendments), challenges in by design (prospective) adaptations, and obstacles of retrospective adaptations are described. Strategies for the use of adaptive design in clinical development of rare diseases are discussed. Some examples concerning the development of Velcade intended for multiple myeloma and non-Hodgkin's lymphoma are given. Practical issues that are commonly encountered when implementing adaptive design methods in clinical trials are also discussed

The relationship between the systemic inflammatory response and survival in patients with transitional cell carcinoma of the urinary bladder

The relationship between tumour stage, grade, elevated C-reactive protein concentration (<10/>10 mg l−1), adjuvant therapy and survival was examined in patients with biopsy proven bladder cancer (n=105). On multivariate analysis stage (HR 3.37, 95% CI 1.37–8.29, P=0.008), grade (HR 2.01, 95% CI 1.14–3.57, P=0.017) and preoperative C-reactive protein (HR 3.31, 95% CI 1.09–10.09, P=0.035) were independently associated with cancer-specific survival