Designing multi‐arm multi‐stage clinical trials using a risk–benefit criterion for treatment selection

Multi‐arm clinical trials that compare several active treatments to a common control have been proposed as an efficient means of making an informed decision about which of several treatments should be evaluated further in a confirmatory study. Additional efficiency is gained by incorporating interim analyses and, in particular, seamless Phase II/III designs have been the focus of recent research. Common to much of this work is the constraint that selection and formal testing should be based on a single efficacy endpoint, despite the fact that in practice, safety considerations will often play a central role in determining selection decisions. Here, we develop a multi‐arm multi‐stage design for a trial with an efficacy and safety endpoint. The safety endpoint is explicitly considered in the formulation of the problem, selection of experimental arm and hypothesis testing. The design extends group‐sequential ideas and considers the scenario where a minimal safety requirement is to be fulfilled and the treatment yielding the best combined safety and efficacy trade‐off satisfying this constraint is selected for further testing. The treatment with the best trade‐off is selected at the first interim analysis, while the whole trial is allowed to compose of J analyses. We show that the design controls the familywise error rate in the strong sense and illustrate the method through an example and simulation. We find that the design is robust to misspecification of the correlation between the endpoints and requires similar numbers of subjects to a trial based on efficacy alone for moderately correlated endpoints. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.     

Phase II clinical trials with time‐to‐event endpoints: optimal two‐stage designs with one‐sample log‐rank test

Phase II clinical trials are often conducted to determine whether a new treatment is sufficiently promising to warrant a major controlled clinical evaluation against a standard therapy. We consider single‐arm phase II clinical trials with right censored survival time responses where the ordinary one‐sample logrank test is commonly used for testing the treatment efficacy. For planning such clinical trials, this paper presents two‐stage designs that are optimal in the sense that the expected sample size is minimized if the new regimen has low efficacy subject to constraints of the type I and type II errors. Two‐stage designs, which minimize the maximal sample size, are also determined. Optimal and minimax designs for a range of design parameters are tabulated along with examples. Copyright © 2013 John Wiley & Sons, Ltd.     

42例老年晚期肺癌并发肺部真菌感染的临床分析

目的 分析老年晚期肺癌合并肺部真菌感染的病原菌构成、耐药性及治疗措施.方法 选择医院2006年6月-2010年12月42例老年晚期肺癌并发肺部真菌感染患者,进行真菌检测及药敏试验,对感染病原菌种类、药敏状况及治疗结果进行分析.结果 42例患者痰培养出真菌42株,其中白色假丝酵母菌24株占57.1％,光滑假丝酵母菌9株占21.4％,热带假丝酵母菌4株占9.5％,克柔假丝酵母菌4株占9.5％,曲霉菌属1株占2.4％;白色假丝酵母菌对氟康唑、5-氟胞嘧啶、伊曲康唑敏感,仅2株对酮康唑耐药,所有菌株均对伊曲康唑敏感;根据真菌培养结果对症治疗后39例好转,再次痰培养结果显示阴性,死亡3例,系合并低蛋白血症、糠尿病及严重贫血,死于多脏器功能衰竭.结论 老年晚期肺癌患者由于肺不张,慢性阻塞性肺疾病等导致肺部易有细菌定植,由于疾病进展或者化疗后,身体免疫力低下,容易继发肺部真菌感染,化疗期间应增加免疫力并密切观察,发现感染,积极治疗,可改善预后.     

One‐stage and two‐stage designs for phase II clinical trials with survival endpoints

This work is motivated by trials in rapidly lethal cancers or cancers for which measuring shrinkage of tumours is infeasible. In either case, traditional phase II designs focussing on tumour response are unsuitable. Usually, tumour response is considered as a substitute for the more relevant but longer‐term endpoint of death. In rapidly lethal cancers such as pancreatic cancer, there is no need to use a surrogate, as the definitive endpoint is (sadly) available so soon. In uveal cancer, there is no counterpart to tumour response, and so, mortality is the only realistic response available. Cytostatic cancer treatments do not seek to kill tumours, but to mitigate their effects. Trials of such therapy might also be based on survival times to death or progression, rather than on tumour shrinkage. Phase II oncology trials are often conducted with all study patients receiving the experimental therapy, and this approach is considered here. Simple extensions of one‐stage and two‐stage designs based on binary responses are presented. Outcomes based on survival past a small number of landmark times are considered: here, the case of three such times is explored in examples. This approach allows exact calculations to be made for both design and analysis purposes. Simulations presented here show that calculations based on normal approximations can lead to loss of power when sample sizes are small. Two‐stage versions of the procedure are also suggested. Copyright © 2014 John Wiley & Sons, Ltd.     

Design and analysis of clinical trials in the presence of delayed treatment effect

In clinical trials with survival endpoint, it is common to observe an overlap between two Kaplan–Meier curves of treatment and control groups during the early stage of the trials, indicating a potential delayed treatment effect. Formulas have been derived for the asymptotic power of the log‐rank test in the presence of delayed treatment effect and its accompanying sample size calculation. In this paper, we first reformulate the alternative hypothesis with the delayed treatment effect in a rescaled time domain, which can yield a simplified sample size formula for the log‐rank test in this context. We further propose an intersection‐union test to examine the efficacy of treatment with delayed effect and show it to be more powerful than the log‐rank test. Simulation studies are conducted to demonstrate the proposed methods. Copyright © 2016 John Wiley & Sons, Ltd.     

Considerations on covariates and endpoints in multi‐arm multi‐stage clinical trials selecting all promising treatments

In early stages of drug development, there is often uncertainty about the most promising among a set of different treatments. To ensure the best use of resources in such situations, it is important to decide which, if any, of the treatments should be taken forward for further testing. In later development, it has been shown that evaluating more than one dose increases the chance of success substantially. In this work, we discuss how multi‐arm multi‐stage trials can be designed such that all promising treatments are kept in the study at the interim analyses. We first investigate the impact of deviating from the planned design and show how confidence intervals can be constructed before we consider the impact of important covariates. We show that under orthogonality, the inclusion of covariates has no effect on familywise error rate control in the strong sense. We further show that the derived methodology can be used to investigate non‐normal endpoints. Copyright © 2012 John Wiley & Sons, Ltd.     

The simultaneous use of weighted logrank and weighted Kaplan–Meier statistics with clustered right‐censored data

Clustered right‐censored data often arise from tumorigenicity experiments and clinical trials. For testing the equality of two survival functions, Jung and Jeong extended weighted logrank (WLR) tests to two independent samples of clustered right‐censored data, while the weighted Kaplan–Meier (WKM) test can be derived from the work of O'Gorman and Akritas. The weight functions in both classes of tests (WLR and WKM) can be selected to be more sensitive to detect a certain alternative; however, since the exact alternative is unknown, it is difficult to specify the selected weights in advance. Since WLR is rank‐based, it is not sensitive to the magnitude of the difference in survival times. Although WKM is constructed to be more sensitive to the magnitude of the difference in survival times, it is not sensitive to late hazard differences. Therefore, in order to combine the advantages of these two classes of tests, this paper developed a class of versatile tests based on simultaneously using WLR and WKM for two independent samples of clustered right‐censored data. The comparative results from a simulation study are presented and the implementation of the versatile tests to two real data sets is illustrated. Copyright © 2009 John Wiley & Sons, Ltd.     

Intention‐to‐treat analysis with treatment discontinuation and missing data in clinical trials

Motivated by a recent National Research Council study, we discuss three aspects of the analysis of clinical trials when participants prematurely discontinue treatments. First, we distinguish treatment discontinuation from missing outcome data. Data collection is often stopped after treatment discontinuation, but outcome data could be recorded on individuals after they discontinue treatment, as the National Research Council study recommends. Conversely, outcome data may be missing for individuals who do not discontinue treatment, as when there is loss to follow up or missed clinic visits. Missing outcome data is a standard missing data problem, but treatment discontinuation is better viewed as a form of noncompliance and treated using ideas from the causal literature on noncompliance. Second, the standard intention to treat estimand, the average effect of randomization to treatment, is compared with three alternative estimands for the intention to treat population: the average effect when individuals continue on the assigned treatment after discontinuation, the average effect when individuals take a control treatment after treatment discontinuation, and a summary measure of the effect of treatment prior to discontinuation. We argue that the latter choice of estimand has advantages and should receive more consideration. Third, we consider when follow‐up measures after discontinuation are needed for valid measures of treatment effects. The answer depends on the choice of primary estimand and the plausibility of assumptions needed to address the missing data. Ideas are motivated and illustrated by a reanalysis of a past study of inhaled insulin treatments for diabetes, sponsored by Eli Lilly. Copyright © 2014 John Wiley & Sons, Ltd.     

放疗合并动脉灌注化疗及栓塞术治疗晚期直肠癌临床观察

目的：采用动脉灌注及栓塞术合并放射治疗晚期直肠癌，与单纯全身静脉化疗法进行比较。方法：采用经皮穿刺髂内动脉或肠系膜下动脉插管灌注化疗药物及栓塞剂，继而采用60Coγ线前后相对野照射，剂量45～50GY／4～5周。对照组采用常规全身静脉化疗。结果：治疗组38例CR＋PR为842％，对照组CR＋PR为37．5％。且年生存率治疗组为64．5％，对照组为31．8％。结论：采用放疗合并动脉灌注化疗及栓塞术治疗晚期直肠癌比单纯全身静脉化疗在生存期、生活质量、症状缓解有较大提高。     

Design and analysis of non‐pharmacological treatment trials with multiple therapists per patient

In trials of physical and talking therapies, nesting of patients within therapists has statistical implications analogous to those of cluster randomised trials. Nevertheless, the clustering effect may be more complex, as it interacts with treatment. For some therapies, individual patients may receive care from multiple therapists of the same type, so that patients are no longer strictly nested within therapists, creating a ‘multiple‐membership’ relationship between patients and therapists. This paper considers methods of analysis and sample size estimation for trials with multiple‐membership clustering effects. It is motivated by a trial of a psychotherapy for the treatment of adolescent depression with cognitive behavioural therapy. We tested methods and issues in a Monte Carlo simulation study, simulating trials with multiple membership. Results demonstrate satisfactory performance in terms of convergence and give estimates of the intra‐cluster correlation coefficient and empirical test size similar to a simple hierarchical design. We derive formulae for sample size and power for multiple‐membership trial designs. We then compare estimates of power from this formula with empirical power derived from the simulation study. Finally, we show that we can easily extend formulae for sample size and power to allow consideration of power and sample size for certain types of more complex interventions. These include situations where therapists of different types deliver separate components of the intervention, creating a cross‐classified relationship, or where several therapists deliver a group‐administered treatment, creating further levels. Copyright © 2012 John Wiley & Sons, Ltd.     

Awareness of diagnosis,treatment and risk of late effects in Chinese survivors of childhood cancer in Hong Kong

BackgroundFor survivors of childhood cancer, awareness of personal health risks is a critical component of long‐term health management.ObjectiveTo evaluate the awareness of the diagnosis, treatment and risk of late effects among survivors of childhood cancer in Hong Kong.MethodsBetween June 2019 and March 2020, this cross‐sectional study recruited 155 adult survivors (mean age = 26.9, standard deviation [SD] = 6.4 years) and 45 parents of paediatric survivors (mean age = 11.1, SD = 3.6 years) from a long‐term follow‐up clinic. At >10 years post‐treatment (mean = 13.4, SD = 7.6 years), they completed a structured questionnaire to report their cancer‐specific knowledge. Multiple linear regression analysis was conducted to identify clinical, socioeconomic and behavioural factors associated with poor awareness.ResultsThe majority of participants accurately recalled their diagnoses (73.5%) and major treatment modalities (chemotherapy 92.4%, radiation 82.9% and surgery 88.2%). However, less than half (45%) of the participants recognized more than 25% of the total late effects for which they were at risk. The highest levels of awareness were reported for endocrine problems (49%), neurocognitive impairment (44%) and secondary cancers (43%), and the lowest for peripheral neuropathy (21%) and vision problems (23%). Compared with survivors of haematological malignancies, those of central nervous system (CNS) tumours (standardized estimate [B] = −9.33, 95% confidence interval [95% CI]: −13.41 to −5.26) and non‐CNS solid tumours (B = −8.47, 95% CI: −12.39 to −4.94) had less knowledge about their diagnosis. Retaining medical records (P < .0001) and better medical information‐seeking habits (P = .048) were associated with better awareness.ConclusionsSurvivors of childhood cancer in Hong Kong have deficient awareness of their personal health risks. They may benefit from the provision of a survivorship care plan and personalized education regarding treatment‐related late effects.Patient ContributionPatients contributed in designing the study tools. Results were presented at a non‐governmental organization.     

A linearization approach for the model‐based analysis of combined aggregate and individual patient data

The application of model‐based meta‐analysis in drug development has gained prominence recently, particularly for characterizing dose‐response relationships and quantifying treatment effect sizes of competitor drugs. The models are typically nonlinear in nature and involve covariates to explain the heterogeneity in summary‐level literature (or aggregate data (AD)). Inferring individual patient‐level relationships from these nonlinear meta‐analysis models leads to aggregation bias. Individual patient‐level data (IPD) are indeed required to characterize patient‐level relationships but too often this information is limited. Since combined analyses of AD and IPD allow advantage of the information they share to be taken, the models developed for AD must be derived from IPD models; in the case of linear models, the solution is a closed form, while for nonlinear models, closed form solutions do not exist. Here, we propose a linearization method based on a second order Taylor series approximation for fitting models to AD alone or combined AD and IPD. The application of this method is illustrated by an analysis of a continuous landmark endpoint, i.e., change from baseline in HbA1c at week 12, from 18 clinical trials evaluating the effects of DPP‐4 inhibitors on hyperglycemia in diabetic patients. The performance of this method is demonstrated by a simulation study where the effects of varying the degree of nonlinearity and of heterogeneity in covariates (as assessed by the ratio of between‐trial to within‐trial variability) were studied. A dose‐response relationship using an Emax model with linear and nonlinear effects of covariates on the emax parameter was used to simulate data. The simulation results showed that when an IPD model is simply used for modeling AD, the bias in the emax parameter estimate increased noticeably with an increasing degree of nonlinearity in the model, with respect to covariates. When using an appropriately derived AD model, the linearization method adequately corrected for bias. It was also noted that the bias in the model parameter estimates decreased as the ratio of between‐trial to within‐trial variability in covariate distribution increased. Taken together, the proposed linearization approach allows addressing the issue of aggregation bias in the particular case of nonlinear models of aggregate data. Copyright © 2014 John Wiley & Sons, Ltd.     

Design of cancer trials based on progression‐free survival with intermittent assessment

Therapeutic advances in cancer mean that it is now impractical to performed phase III randomized trials evaluating experimental treatments on the basis of overall survival. As a result, the composite endpoint of progression‐free survival has been routinely adopted in recent years as it is viewed as enabling a more timely and cost‐effective approach to assessing the clinical benefit of novel interventions. This article considers design of cancer trials directed at the evaluation of treatment effects on progression‐free survival. In particular, we derive sample size criteria based on an illness‐death model that considers cancer progression and death jointly while accounting for the fact that progression is assessed only intermittently. An alternative approach to design is also considered in which the sample size is derived based on a misspecified Cox model, which uses the documented time of progression as the progression time rather than dealing with the interval censoring. Simulation studies show the validity of the proposed methods.     

Results and DVH analysis of late rectal bleeding in patients treated with 3D-CRT or IMRT for localized prostate cancer

In patients undergoing radiotherapy for localized prostate cancer, dose–volume histograms and clinical variables were examined to search for correlations between radiation treatment planning parameters and late rectal bleeding. We analyzed 129 patients with localized prostate cancer who were managed from 2002 to 2010 at our institution. They were treated with 3D conformal radiation therapy (3D-CRT, 70 Gy/35 fractions, 55 patients) or intensity-modulated radiation therapy (IMRT, 76 Gy/38 fractions, 74 patients). All radiation treatment plans were retrospectively reconstructed, dose–volume histograms of the rectum were generated, and the doses delivered to the rectum were calculated. Time to rectal bleeding ranged from 9–53 months, with a median of 18.7 months. Of the 129 patients, 33 patients had Grade 1 bleeding and were treated with steroid suppositories, while 25 patients with Grade 2 bleeding received argon plasma laser coagulation therapy (APC). Three patients with Grade 3 bleeding required both APC and blood transfusion. The 5-year incidence rate of Grade 2 or 3 rectal bleeding was 21.8% for the 3D-CRT group and 21.6% for the IMRT group. Univariate analysis showed significant differences in the average values from V65 to V10 between Grades 0–1 and Grades 2–3. Multivariate analysis demonstrated that patients with V65 ≥ 17% had a significantly increased risk (P = 0.032) of Grade 2 or 3 rectal bleeding. Of the 28 patients of Grade 2 or 3 rectal bleeding, 17 patients (60.7%) were cured by a single session of APC, while the other 11 patients required two sessions. Thus, none of the patients had any further rectal bleeding after the second APC session.     

食管癌、胃癌并上消化道出血的内镜治疗效果分析

目的：探讨食管癌、胃癌出血的内镜治疗效果。方法将84例确诊为食管癌、胃癌出血的患者，随机分为A、B、C三组，每组28例。三组均给予一般常规治疗，A组在此基础上予内镜下金属止血夹钳夹止血疗法；B组予内镜下局部药物注射疗法，C组予内镜下微波止血疗法，比较三组的治疗效果。结果A组首次止血成功率显著高于B组及C组（χ2=9.108，P=0.0025及χ2=12.163，P=0.0005）；A组再出血率显著低于B组及C组（χ2=5.965，P=0.0145及χ2=7.24，P=0.0071）。结论内镜下金属止血夹治疗食管癌、胃癌出血的首次止血成功率高、再出血率低，值得临床上推广应用。     

Alternative definitions of comparable case groups and estimates of lead time and benefit time in randomized cancer screening trials

Randomized screening trials provide the optimal means of assessing the benefit of screening for cancer and other chronic diseases. Unlike therapy trials, however, where strict eligibility criteria assure the comparability of cases of disease in the arms of the trial, the cancer cases identified during follow-up are a subset of all randomized participants. Furthermore, those cases detected by screening tend to arise from length biased sampling which also can bias estimates of the screening benefit and of average lead time. To reduce or eliminate this bias, we propose several methods for defining comparable groups of cases from the trial arms. We examine, via simulation, these methods with respect to their effects on (i). point and interval estimates of average lead time and average benefit time and (ii). the logrank test statistic for a mortality effect of screening. The most successful new method for defining comparable case groups uses an estimate of the mean sojourn time (mean preclinical duration), and results in nearly unbiased estimates of average lead time and average benefit time as well as an unbiased logrank test statistic.     

Estimation in multi‐arm two‐stage trials with treatment selection and time‐to‐event endpoint

We consider estimation of treatment effects in two‐stage adaptive multi‐arm trials with a common control. The best treatment is selected at interim, and the primary endpoint is modeled via a Cox proportional hazards model. The maximum partial‐likelihood estimator of the log hazard ratio of the selected treatment will overestimate the true treatment effect in this case. Several methods for reducing the selection bias have been proposed for normal endpoints, including an iterative method based on the estimated conditional selection biases and a shrinkage approach based on empirical Bayes theory. We adapt these methods to time‐to‐event data and compare the bias and mean squared error of all methods in an extensive simulation study and apply the proposed methods to reconstructed data from the FOCUS trial. We find that all methods tend to overcorrect the bias, and only the shrinkage methods can reduce the mean squared error. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.