Operating characteristics of sample size re-estimation with futility stopping based on conditional power

Standard Operating Procedures for Chinese Medicine Data Monitoring Committees of Clinical Studies

Although there is guidance from different regulatory agencies, there are opportunities to bring greater consistency and stronger applicability to address the practical issues of establishing and operating a data monitoring committee (DMC) for clinical studies of Chinese medicine. We names it as a Chinese Medicine Data Monitoring Committee (CMDMC). A panel composed of clinical and statistical experts shared their experience and thoughts on the important aspects of CMDMCs. Subsequently, a community standard on CMDMCs (T/CACM 1323-2019) was issued by the China Association of Chinese Medicine on September 12, 2019. This paper summarizes the key content of this standard to help the sponsors of clinical studies establish and operate CMDMCs, which will further develop the scientific integrity and quality of clinical studies.

The contemplated average success probability for normally distributed models with an application to optimal sample sizes selection

We analytically obtain the average success probability (ASP) and the contemplated average success probability (CASP) for normally distributed observed differences in the treatment group and the placebo group means of the early trial and the confirmatory trial, assuming a uniform noninformative prior for the population treatment effect and a common known variance of the observations from both groups. For the CASP optimization problem with a fixed subtotal sample size of the early trial and the confirmatory trial of one arm larger than a threshold, we obtain the optimal plan of the sample sizes in a theorem. Moreover, in the theorem, we obtain the analytical formula of the optimal CASP as an increasing function of the subtotal sample size. After that, we calculate and compare the numerical values of the ASP with those in Table 1 of Chuang-Stein (2006). Finally, we investigate the numerical features of the CASP and find the optimal plan of the sample sizes for a given subtotal sample size.

Three-component cure rate model for nonproportional hazards alternative in the design of randomized clinical trials

BACKGROUND

Cure rate models have been extensively studied and widely used in time-to-event data in cancer clinical trials.

PURPOSE

Although cure rate models based on the generalized exponential distribution have been developed, they have not been used in the design of randomized cancer clinical trials, which instead have relied exclusively on two-component exponential cure rate model with a proportional hazards (PH) alternative. In some studies, the efficacy of the experimental treatment is expected to emerge some time after randomization. Since this does not conform to a PH alternative, such studies require a more flexible model to describe the alternative hypothesis.

METHODS

In this article, we report the study design of a phase III clinical trial of acute myeloid leukemia using a three-component exponential cure rate model to reflect the alternative hypothesis. A newly developed power calculation program that does not require PH assumption was used.

RESULTS

Using a custom-made three-component cure rate model as an alternative hypothesis, the proposed sample size was 409, compared with a sample size of 209 under the assumption of exponential distribution and 228 under the PH alternative. A simulation study was performed to present the degree of power loss when the alternative hypothesis is not appropriately specified.

LIMITATIONS

The power calculation program used in this study is for a single analysis and does not account for group sequential tests in phase III trials. However, the loss in power is small, and this was handled by inflating the sample size by 5%.

CONCLUSION

Misspecification of the alternative hypothesis can result in a seriously underpowered study. We report examples of clinical trials that required a custom-made alternative hypothesis to reflect a later indication of experimental treatment efficacy. The proposed three-component cure rate model could be very useful for specifying non-PH alternative.

Failure to preserve beta-cell function with mycophenolate mofetil and daclizumab combined therapy in patients with new- onset type 1 diabetes

OBJECTIVE

This trial tested whether mycophenolate mofetil (MMF) alone or with daclizumab (DZB) could arrest the loss of insulin-producing beta-cells in subjects with new-onset type 1 diabetes.

RESEARCH DESIGN AND METHODS

A multi-center, randomized, placebo-controlled, double-masked trial was initiated by Type 1 Diabetes TrialNet at 13 sites in North America and Europe. Subjects diagnosed with type 1 diabetes and with sufficient C-peptide within 3 months of diagnosis were randomized to either MMF alone, MMF plus DZB, or placebo, and then followed for 2 years. The primary outcome was the geometric mean area under the curve (AUC) C-peptide from the 2-h mixed meal tolerance test.

RESULTS

One hundred and twenty-six subjects were randomized and treated during the trial. The geometric mean C-peptide AUC at 2 years was unaffected by MMF alone or MMF plus DZB versus placebo. Adverse events were more frequent in the active therapy groups relative to the control group, but not significantly.

CONCLUSIONS

Neither MMF alone nor MMF in combination with DZB had an effect on the loss of C-peptide in subjects with new-onset type 1 diabetes. Higher doses or more targeted immunotherapies may be needed to affect the autoimmune process.

Impact of interleukin 6 -174G>C polymorphism on obesity-related metabolic disorders in people with excess in body weight

Low-grade inflammation has been related to obesity, insulin resistance, and related metabolic disorders. In this context, the -174G>C gene polymorphism of the proinflammatory interleukin 6 (IL-6) cytokine has also been associated with these diseases. Based on this, the aim of the current study was to evaluate the role of IL-6 -174G>C polymorphism in the risk of developing metabolic alterations in people with excessive body weight. One hundred six Caucasian volunteers (body mass index, 33.2 +/- 5.3 kg/m(2)) were recruited to assess the potential relationship between carrying the -174G>C polymorphism and the risk of developing obesity-related metabolic disorders, such as hypertension, atherogenic dyslipidemia, and insulin resistance evaluated by the homeostasis model assessment of insulin resistance index. Subjects carrying the C allele showed higher plasma insulin concentrations and systolic blood pressure than homozygotes for the G allele. A multiple regression analysis showed that the presence of the C allele induced an increase in the homeostasis model assessment of insulin resistance index as compared with GG subjects (adjusted R(2) = .26, P < .001). Analyzing the mentioned obesity-related diseases, an enhanced prevalence of presenting high risk of developing these complications was found for the GC and CC genotypes relative to GG, with an adjusted odds ratio of 5.2 (P = .003). This association remained significant after controlling for multiple comparisons by the 10,000-permutation test (P = .004838). These data demonstrate that the occurrence of C allele of IL-6 -174 G>C gene polymorphism in people with excessive body weight is accompanying a higher risk of developing obesity-related metabolic disorders, especially insulin resistance.