With the transformation of modern medical models, patient-reported outcomes, clinician-reported outcomes, observer-reported outcomes, and performance outcomes have become internationally recognized clinical outcome assessment indicators, and scales have also become important evaluation tools, among which translation and cross-cultural adaptation are one of the important sources of scales. However, at present, there are fewer guidelines for scale translation in China. At present, domestic scale translation has not yet been unified and standardized in clinical reporting. Most translation reports provide readers with incomplete information, which affects the development of scale translation, and the methodology related to the translation of clinical outcome assessment scales still focuses on patient-reported outcome scales, which creates a gap in terms of the recommendations for the rest of the types of translations, a gap which leads to inconsistencies in the translation methodology and process. In this paper, we will develop specific translation methods and processes for each of the four current types of clinical outcome assessments by combining scale translation guidelines to support a standardized approach to translation, cross-cultural adaptation, and linguistic validation for use in standardizing the process of recommending translations of patient-reported outcome scales, clinical-reported outcome scales, observer-reported outcome scales, and behavioral outcome scales.
In recent years, clinical research in traditional Chinese medicine (TCM) has witnessed vigorous development, with increasingly close integration with clinical epidemiological methodologies. However, certain controversies persist, such as the difficulty in aligning epidemiology’s population-based perspective with TCM’s principle of syndrome differentiation and treatment and the characteristics of individualized diagnosis and treatment. This paper reviews the development and current status of TCM clinical research, integrating the practice rules of TCM, and analyzes the manifestations and applicability of the basic characteristics of epidemiology in TCM clinical research. The study shows that epidemiological concepts and characteristics are fully compatible with the practical features of TCM clinical practice and its research needs. Moreover, epidemiological techniques can effectively uncover and elucidate the scientific basis of TCM clinical practice. Building on these analyses, we propose future directions for TCM clinical research, aiming to promote the integration of epidemiology and TCM clinical research and advance TCM clinical research to a higher level.
Sample size re-estimation (SSR) refers to the recalculation of the sample size using the existing trial data as original planned to ensure that the final statistical test achieved the pre-defined goals. SSR can enhance research efficiency, save trial costs, and accelerate the research process. Depending on whether the group assignment of the patients is known, SSR is divided into blinded sample size re-estimation and unblinded sample size re-estimation. Blinded sample size re-estimation can estimate the variance of the primary evaluation index through the EM algorithm or single sample variance re-estimation method, and then calculate the sample size. Unblinded sample size re-estimation can calculate the sample size by estimating the overall variance or therapeutic effect difference, but it needs to control the family wise type I error (FWER) rate. Cui-Hung-Wang method, conditional rejection probability method, P-value combination method, conditional error function, and promising zone are common methods used to control FWER. Currently, there are application examples of SSR methods. With the maturation of related theories and the popularization of methods, it is expected to be widely applied in clinical trials, especially in traditional Chinese medicine clinical trials in the future.
ObjectiveTo systematically investigate the application status of the minimal clinically important difference (MCID) and minimal important change (MIC) in intragroup and intergroup analyses of functional constipation symptom scales from 2000 to 2025, and provide a reference for the standardized formulation of clinical efficacy evaluation criteria for functional constipation in China. MethodsRandomized controlled trials (RCTs) and meta-analyses on functional constipation were retrieved from WanFang Data, CNKI, PubMed, Embase, and CENTRAL databases between January 1, 2000, and January 7, 2025. Three reviewers independently screened the literature, extracted information on the characteristics of MIC/MCID reported in the studies, and conducted descriptive analyses. ResultsA total of 337 studies were evaluated for readability, with 291 studies meeting the inclusion criteria. Among eligible studies, 6 used MIC/MCID thresholds, and 38 reported responder definitions, including 5 using MIC and 1 using MIC and MCID. Discrepancies were observed between the expected and actual values of MIC/MCID. Six included studies provided explicit citation support for their selected MIC/MCID thresholds. ConclusionThe application and interpretation of MIC and MCID thresholds face fundamental challenges. Using functional constipation research as an example, researchers often derive MIC-like thresholds through intergroup comparisons of individual change proportions and mistakenly equate them with MCID. This conceptual confusion may lead to clinical interpretation bias due to neglecting the essential differences between the two thresholds. Additionally, issues include lack of methodological justification for responder analysis, broad threshold ranges, and near-absence of blinded evaluations. It is recommended that researchers clarify the definitions and analytical pathways of the two thresholds during RCT design, avoid misusing intergroup statistics as individual efficacy criteria, and strengthen the methodological rigor of blinded design and threshold validation.
