Increase the probability of your products’ success

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Presentation transcript:

Increase the probability of your products’ success SAS Report Writing Interface vs R Markdown for Patient Profile Generation Qin Meng 缔结创新之脉,助力成功之道 Increase the probability of your products’ success August 31, 2019

Bio Qin Meng, Associate Manager, Statistical Programming from dMed Nine years of clinical programming experience, covering many therapeutic areas, especially oncology studies. Responsible for Clinical Study Report in CDISC Developing the programs for CDISC datasets automation, Patient Profiles, Study Oversight for data monitoring etc. New employee trainings

Process of Patient Profile Generation SAS ODS Report Writing Interface RMarkdown in RStudio Conclusion

Process of Patient Profile Generation

Patient profile Patient profile report for the clinical trial studies displays the collected original data and information within tables or graphs. One patient profile report is generated for only one patient. According to the types or purposes of different clinical trials, different designs will be performed for the patient profile. 12/6/2019

Generation Process Step 1 Step 3 Step 2 Patient Profile Data extraction Source Data review Patient Profile design Step 2 Validation is needed Update according to the requirements (from customer) Subject ID selection Run the program to generate the report (SAS ODS RWI/Rmarkdown) File format conversion, usually PDF is reasonable 12/6/2019

Generation Process 12/6/2019

Generation Process – Profile Design Different clinical trials, different designs For Phase I, dose escalation and research studies, the researchers will show their interests to the patients’ adverse events especially the DLT (dose limited tolerate) events. For these purposes, the patient profile will be designed to display their safety status and DLT events on the cover page, and better to include more details for the parts of safety in the report For data monitoring and data quality review, the patient profile report needs to be designed for the CRF (case report form) data, as much as collected data should be included and it’s better to be sorted by visits in the reporting file. For oncology studies, the PFS and OS related results and RECIST (Response Evaluation Criteria in Solid Tumors) results are expected to be collected, calculated and displayed on the cover page, as well as in the tumor assessment parts in the report. 12/6/2019

Generation Process Cover Page of Patient Profile Shows the basic and key information of subject in clinical trial studies 12/6/2019

Generation Process - Table of Contents Table of Contents could be automatically generated by program 12/6/2019

SAS ODS Report Writing Interface

SAS ODS Report Writing Interface Advantages of SAS ODS RWI Fully embrace ODS features, including fonts, colors, images, lines, titles etc. Rich programming features of DATA step, including conditional sentences, formatting capabilities, by-group processing, do- loops programming etc. Object-oriented language, it can provide us the flexibility. 12/6/2019

Example – SAS ODS RWI data _null_; obj.row_start(); set class; by sex name; where name eq "Thomas";   if _N_ = 1 then do; dcl odsout obj(); end; if first.sex then do; obj.table_start(); obj.head_start(); obj.row_start(); obj.format_cell(data: "Name", row_span: 3, vjust: "B"); obj.format_cell(data: sex, column_span: 4, format: "$gender."); obj.row_end(); obj.format_cell(data: "Age", row_span: 2, vjust: "B"); obj.format_cell(data: "Vitals", column_span: 3); obj.row_start(); obj.format_cell(data: "Height"); obj.format_cell(data: "Weight"); obj.format_cell(data: "BMI"); obj.row_end();   obj.head_end(); end; bmi = ( weight / ( height * height ) ) * 703; obj.format_cell(data: name); obj.format_cell(data: age); obj.format_cell(data: height); obj.format_cell(data: weight); obj.format_cell(data: bmi, format: "8.2"); if last.sex then do; obj.table_end(); run; ods rtf close; ods rtf; 12/6/2019

Example – SAS ODS RWI 12/6/2019

Rmarkdown in Rstudio 需要承上启下一下

Rmarkdown in Rstudio Advantages of Rmarkdown R Markdown is recommended to generate high quality reports. R Markdown documents are fully reproducible and support dozens of static and dynamic output formats. Fully embrace ODS features, including fonts, colors, images, lines, titles etc. There is a new definition in Rmarkdown called “code chunks”, R code chunks are surrounded by ```s. We can run each code chunk by clicking the “ ” icon. RStudio executes the code and display the results consistent with our file. We can also embed plots with R markdown, for example, ggplot can be used to generate visualized and interactive graphs. When you move your pointer to the dots in the plots, the values will be shown accordingly. Play icon 12/6/2019

Example - Rmarkdown 12/6/2019

Example - Rmarkdown Click to run Click to exit 12/6/2019

Example - Rmarkdown 12/6/2019

Conclusion Comparing SAS ODS Report Writing Interface with R Markdown for patient profile, both methods have their advantages. SAS program might be familiar and formal to use and run. When we want the report in an interactive manner, Rmarkdown is a better choice. Both SAS ODS Report Writing Interface and R Markdown are suggested to be used in the process of patient profile generation, they always can meet your requirements easily and effectively. 12/6/2019

Thank you for Your Time ! Name: Qin Meng Company: dMed Biopharmaceutical Co., Ltd.   Address: Wuhan, China E-mail: qin.meng@dmedglobal.com Phone: +86 13871387052