Source data and its source documents are the foundation of clinical research. Proper source data management plays an essential role for compliance with regulatory and GCP requirements. Both paper and electronic source data co-exist in China. Due to the increasing use of electronic technology in pharmaceutical and health care industry, electronic data source becomes an upcoming trend with clear advantages. To face new opportunities and to ensure data integrity, quality and traceability from source data to regulatory submission, this document demonstrates important concepts, principles and best practices during managing source data. It includes but not limited to: (1) important concepts of source data (e.g., source data originator, source data elements, source data identifier for audit trail, etc.); (2) various modalities of source data collection in paper and electronic methods (e.g., paper CRF, EDC, Patient Report Outcomes/eCOA, etc.); (3) seven main principles recommended in the aspect of data collection, traceability, quality standards, access control, quality control, certified copy and security during source data management; (4) a life cycle from source data creation to obsolete is used as an example to illustrate consideration and implementation of source data management.

With the deployment of electronic medical records systems, more and more routine clinical data are recorded electronically, which become a potential data source for new drug clinical trials. In this paper, we summarized the opportunities, challenges, obstacles and the latest development in this field.

CDISC standard has become a set of global data standards that can be used in clinical study, covering the full life cycle of clinical researches. After nearly 20 years of development and continuous version upgrades, CDISC standard can improve the quality and efficiency of clinical research and drug review, and to facilitate all stakeholders involved in researches to exchange the study data and communicate the outcomes. CDISC standard has been or is to be adopted as standard format in data submission by multiple regulatory authorities, and more widely implemented by the global pharmaceutical community. CDISC standard is gradually adopted in China. The feasibility and roadmap of CDISC standard as the Chinese data submission format requirements are undergoing exploration and piloting further.

Objective:To construct an effective survival nomogram for patients with clear cell renal cell carcinoma (ccRCC) using a large sample sized Chinese dataset, which can be used to predict individual 3- and 5-year overall survival (OS) precisely.Methods:The data of 672 ccRCC patients received operation diagnosed at Xijing Hospital from January 2012 to December 2016 were retrospectively analyzed. There were 467 males and 205 females. Their median age was 56 years old (ranging 23-83 years old). There were 327 patients with tumor on the left kidney and 345 patients with tumor on the right kidney. Clinical stageⅠ, Ⅱ, Ⅲ, Ⅳ were 584, 47, 19 and 22 cases, respectively. At the time of diagnosis, 504 patients were asymptomatic and 168 patients were symptomatic. Preoperative alkaline phosphatase was 80 (41-240) U/L. Preoperative serum albumin was 44.8 (30.5-59.8) g/L. Preoperative neutrophil absolute value/lymphocyte absolute value (NLR) was 2.25 (0.81-9.89). Preoperative platelet count was 205 (82-589)×10 9/L. Preoperative creatinine was 97 (55-230) μmol/L. Radical nephrectomy was performed in 420 (62.5%) patients and partial nephrectomy was performed in 252 patients. Cox multivariate analysis was used to determine the independent predictors of the postoperative OS. Then, the nomogram was constructed using R software, which integrates all independent predictors according to the coefficients in the multivariate analysis. Moreover, the performance of the nomogram was evaluated using the consistency index (C-index) and the calibration plots. Results:Cox multivariate analysis results showed that age at diagnosis ( P<0.001), clinical TNM stage ( P<0.001), preoperative NLR ( P=0.012), preoperative alkaline phosphatase ( P=0.002) and preoperative albumin ( P<0.001) were the independent predictors of postoperative OS in ccRCC patients. The nomogram established by integrating these five factors had a good discriminatory ability (C-index=0.819, 95% CI 0.813-0.825), and the calibration plots showed that excellent agreements between the nomogram prediction and the actual observation were achieved. Conclusions:Based on a large sample sized Chinese dataset, this study established an effective survival model for patients with ccRCC and good performance of the nomogram was demonstrated by internal validation. Our nomogram can help urologists to predict individual 3- and 5-year OS accurately for Chinese ccRCC patients.