Research of generating real-world evidence using real world data has attracted considerable attention globally. Outcome research of treatment based on existing health and medical data or registries has become one of the most important topics. However, there exists certain confusions in this line of research on how to design and implement appropriate statistical analysis. Therefore, in the fourth chapter of the series technical guidance to develop real world evidence by China REal world data and studies Alliance (ChinaREAL), we aim to provide an guidance on statistical analysis in the study to assess therapeutic outcomes based on existing health and medical data or registries.In this chapter, we first emphasize the significance of pre-specified statistical analysis plan, recommending key components of the statistical analysis plan. We then summarize the issue of sample size calculation in this content and clarify the interpretation of statistical p-value. Secondly, we recommend procedures to be considered to tackle the issue related to the selection bias, information bias and most importantly, confounding bias. We discuss the multivariable regression analysis as well as the popular causal inference models. We also suggest that careful consideration should be made to deal with missing data in real-world databases. Finally, we list core content of the statistical report.
ObjectiveTo evaluate the combination efficacy with Qingfei Yihuo capsule and routine antibiotics as well as mucopolytic agents in the treatment of bronchiectasis acute exacerbation.MethodsThis was a prospective, multi-center, randomized controlled clinical study. The efficacy of Qingfei Yihuo capsule combine with routine antibiotics and mucopolytic agents in the treatment of bronchiectasis acute exacerbation was compared according to the symptom control as well as exacerbation duration. Through randomization, patients received Qingfei Yihuo capsule or placebo combine with routine antibiotics and mucopolytic agents treatment for 10 days. Symptom score of cough, sputum, short of breath pre- and post-treatment as well as the symptom score in daily card were compared between the two groups. The spirometry and St. George respiratory questionnaire (SGRQ) before and after treatment were compared.ResultsThis study was conducted from June 2017 to August 2018. One hundred and ninety patients from 7 centers in 6 hospitals with bronchiectasis acute exacerbation were enrolled in the study. There was statistically improvement of symptom score (including the 9th and 10th treatment days) according to the daily card recording in Qingfei Yihuo capsule group compared to the placebo group, but no statistically significant difference was found in spirometry results or SGRQ.ConclusionQingfei Yihuo capsule has assistant effect on improving respiratory symptoms of bronchiectasis exacerbation.
Traditional Chinese medicine (TCM) has a long history. In the process of fighting against diseases, TCM has formed a unique theoretical system and the way to think and diagnose. The holistic thinking, and the treatment according to syndrome differentiation are the most prominent characteristics of TCM, which matches with advanced medical concept and direction. The clinical efficacy has always been the basis for the advancement of TCM. However, issues such as the lagging behind of modern research on the evaluation of TCM curative effect, as well as lacking high-quality scientific research evidence, impede the development and promotion of the TCM toward the world. To address the above problems, recent progress in real-word study (RWS) has provided the opportunity for TCM researches, especially for the post-marketing evaluation of Chinese patent medicine (CPM). The formulation of this technical guidance for RWS of CPM is helpful to researchers in carrying out standardized, reasonable and scientific researches, to improve the quality of production and use of real-word evidence, and to promote the advancement of the TCM industry.
With the boom of information technology and data science, real-world evidence (RWE) which is produced using diverse real-world data (RWD) has become an important source for healthcare practice and policy decisions, such as regulatory and coverage decisions, guideline development, and disease management. The production of high-quality RWE requires not only complete, accurate and usable data, but also scientific and sound study designs and data analyses to enable the questions of interest to be reliably answered. In order to improve the quality of production and use of RWE, China REal world data and studies ALliance (ChinaREAL) has developed the first series of technical guidance for developing real-world data and subsequent studies. The efforts are ongoing which would ultimately inform better healthcare practice and policy decisions.