How Assessment-Schedule Matching Limits Bias When Comparing Progression-Free Survival in Single-Arm Studies: An Application in Second-Line Urothelial Carcinoma Treatments

ObjectivesPopulation-adjusted comparisons of progression-free survival (PFS) from single-arm trials of cancer treatments can be derived using matching-adjusted indirect comparisons (MAICs); however, results are still susceptible to bias, particularly if the trials had different tumor assessment schedules. This study aims to assess the effects of assessment-schedule matching (ASM) on the relative effectiveness on the PFS of avelumab versus approved comparator immunotherapies or chemotherapy after population matching in the second-line (2L) setting for metastatic urothelial carcinoma.MethodsThe MAIC used patient-level data for avelumab from the JAVELIN Solid Tumor trial (NCT01772004). PFS was compared with published curves for other treatments to obtain population-adjusted hazard ratios (HRs). The MAIC was repeated after conducting ASM for differences in tumor assessment scheduled first at 6 weeks for avelumab and durvalumab and at 8 or 9 weeks for other treatments.ResultsMAIC adjustment alone altered the HR estimates up to 23%, whereas MAIC plus ASM resulted in up to 32.7% reductions from naive comparisons. Even in cases in which MAIC had little effect, ASM brought an additional change of 11.1% to 15.4%. Overall, the HR range of avelumab versus other treatments changed from 0.83 to 1.25 for naive comparisons to 0.76 to 0.99 after ASM plus MAIC, numerically favoring avelumab.ConclusionsSmall variations in assessment schedules can introduce bias in unanchored indirect treatment comparisons of interval-censored time-to-event outcomes. In this study, adjusted PFS was comparable across second-line urothelial carcinoma treatment options, numerically favoring avelumab versus immunotherapies and chemotherapy agents. Correcting this bias is especially important when HRs are applied in cost-effectiveness models to transition patients between states.     

仁青常觉治疗卵巢癌的作用研究

目的：观察藏药仁青常觉治疗卵巢癌的作用。方法：通过对仁青常觉体及其含药血清体外对卵巢癌细胞的抑制作用实验研究,采用MTT法测定细胞存活率,比较各实验组的细胞生长抑制状况,观察仁青常觉治疗卵巢癌的作用。结果：仁青常觉可以抑制卵巢癌细胞的生长,效果与顺铂相当。结论：仁青常觉有治疗卵巢癌的作用。     

Multiplicity Issues in Clinical Trials With Multiple Objectives

Modern clinical trials for evaluating efficacy and safety of new treatments frequently include multiple objectives with questions of varying clinical importance. Answering them generally requires performing a number of statistical tests and analyses which raise multiplicity of tests issues. These issues can be complex and multidimensional in nature. For example, one dimension may relate to the assessment of the effects of the treatment on multiple endpoints, the other to the effects of multiple doses of the treatment, and yet another to the type of the tests (e.g., superiority or noninferiority-type tests). Also, the trial may seek claims for treatment benefits either for the total patient population or for targeted subgroups. In addition, there may be interest in finding whether or not a certain consistency of results persists across certain multiple endpoints; in some situations this may be measuring different but critical features of a disorder, or in other situations may be measuring the same underlying pathophysiology of the disorder. Addressing such problems in clinical trials for the purpose of controlling the Type I error rate requires the use of advanced statistical test strategies and methods, some of which have only recently appeared. Actually, the last decade has witnessed a number of novel methods as well as innovative extensions of old methods for addressing complex multiplicity problems in clinical trials. The main purpose of this article is to present—at the conceptual level—how multiplicity issues of confirmatory clinical trials that include multiple objectives can be addressed by using some of these new statistical methods that use α-propagation and gatekeeping concepts. One additional goal of this contribution is to address some issues that often arise in the use of coprimary and composite endpoints in clinical trials.     

More on the means comparison with unequal variances problem

Scheffe gave an exact solution to the problem of comparing two means from normal populations with unequal variances that is useful for general analysis of variance problems. The behavior of the usual t-statistic that assumes equal variances is contrasted to Satterthwaite's approximate t- statistic and Scheffe's method. An interesting relationship is uncovered between Scheffe's and Satterthwaite's solutions.     

Is it possible to make cross-study comparisons of urinary continence rates in patients with overactive bladder?

ABSTRACT

Several antimuscarinic agents are available for the treatment of overactive bladder but there are few head-to-head studies to guide physicians in choosing one over another. Here we propose ways in which logical adjustments can be made to account for differences in disease severity and placebo effects when considering continence data to allow estimation of relative effectiveness across studies.     

ADJUSTING PAIRWISE NONPARAMETRIC EQUIVALENCE HYPOTHESIS TESTS AND CONFIDENCE INTERVALS FOR PERIOD EFFECTS IN 3×3 CROSSOVER TRIALS

In pharmacokinetic and pharmacodynamic 3×3 crossover trials, average bioequivalence and noninferiority between treatments need to be only assessed pairwise in most cases. Due to the restricted number of subjects in such trials, normal distribution assumptions cannot be checked and frequently outliers are encountered, so that a nonparametric approach is more adequate. Therefore, to assess average bioequivalence or noninferiority, a new method is proposed to derive period adjusted nonparametric confidence intervals for pairwise treatment differences.     

Indirect Treatment Comparison/Network Meta-Analysis Study Questionnaire to Assess Relevance and Credibility to Inform Health Care Decision Making: An ISPOR-AMCP-NPC Good Practice Task Force Report

Despite the great realized or potential value of network meta-analysis of randomized controlled trial evidence to inform health care decision making, many decision makers might not be familiar with these techniques. The Task Force developed a consensus-based 26-item questionnaire to help decision makers assess the relevance and credibility of indirect treatment comparisons and network meta-analysis to help inform health care decision making. The relevance domain of the questionnaire (4 questions) calls for assessments about the applicability of network meta-analysis results to the setting of interest to the decision maker. The remaining 22 questions belong to an overall credibility domain and pertain to assessments about whether the network meta-analysis results provide a valid answer to the question they are designed to answer by examining 1) the used evidence base, 2) analysis methods, 3) reporting quality and transparency, 4) interpretation of findings, and 5) conflicts of interest. The questionnaire aims to help readers of network meta-analysis opine about their confidence in the credibility and applicability of the results of a network meta-analysis, and help make decision makers aware of the subtleties involved in the analysis of networks of randomized trial evidence. It is anticipated that user feedback will permit periodic evaluation and modification of the questionnaire.     

Cultural/Ethnic Comparisons: A Research Agenda

This paper outlines some of the common problems encountered by researchers conducting ethnic or cultural comparisons. The problems are considered in relation to three linked questions that are considered with respect to a comparison of Irish-American and mainland Puerto Rican drinking behavior. With regard to the first question—whom to compare in such research— attention is drawn to the importance of selecting groups on conceptual grounds rather than on the basis of convenience or availability. The distinction between model- and meaning-driven choices is then highlighted. Problems associated with group designation, inclusion criteria, and confounding are also discussed in response to this first question. With respect to the second question—what to compare in such research—the discussion focuses on model-driven measures and generalization-driven measures and the issue of acculturation. The final question—how to insure measure comparability—is addressed with respect to measure equivalence, the problem of cross-cultural meaning and significance, and the use of backtranslation methods to insure linguistic equivalence.     

参加5次医疗器械比对实验的回顾与体会

对5次参与国家医疗器械实验室问比对实验的回顾．总结了参加比对实验的经验和体会．并提出了几点建议。