| PHUSE EU |
2025 |
Visualising the Invisible: Patient Journey with Waterfall, Spider and Swimmer Plots |
Varsha Mithun Patil,
Sunita Poojary |
source
presentation source |
14 |
| SESUG |
2025 |
Building Complex Graphics from Simple Plot Types |
Dan Heath |
|
17 |
| PharmaSUG |
2025 |
Integrated R scripts to Power BI |
Jun Yang |
source |
6 |
| PharmaSUG |
2025 |
Visualizing oncology data through 3D bar charts in R and Python |
Girish Kankipati,
Venkatesulu Salla |
source |
18 |
| PharmaSUG CN |
2024 |
Best Overall Response (BOR) Confirmation in Oncology Clinical Trials: Insights from RECIST 1.1 |
Jihai Li |
source |
15 |
| PharmaSUG |
2024 |
Building Complex Graphics from Simple Plot Types |
Dan Heath |
source |
17 |
| WUSS |
2023 |
Waterfall vis a vis Spider plots: Complex oncology efficacy endpoint made simpler. |
Yoganand Budumuru |
source |
21 |
| PharmaSUG |
2023 |
Leverage and Enhance CDISC TAUGs to Build More Traceability for and Streamline Development of Efficacy ADaM in Oncology Studies |
Xiangchen (Bob) Cui |
source |
29 |
| PharmaSUG |
2022 |
Derivation of Efficacy Endpoints by iRECIST Criteria: A Practical Approach |
Ilya Krivelevich,
Lei Gao,
Richard Kennan |
source |
9 |
| PharmaSUG |
2020 |
Butterfly Plot for Comparing Two Treatment Responses |
Raghava Pamulapati |
source |
13 |
| PharmaSUG |
2020 |
Calculation of Cochran-Mantel-Haenszel Statistics for Objective Response and Clinical Benefit Rates and the Effects of Stratification Factors |
Girish Kankipati,
Chia-Ling (Ally) Wu |
source |
8 |
| PharmaSUG |
2020 |
CDISC-compliant Implementation of iRECIST and LYRIC for Immunomodulatory Therapy Trials |
Kuldeep Sen,
Sumida Urval,
Yang Wang |
source |
11 |
| PharmaSUG |
2020 |
Simplifying the Derivation of Best Overall Response per RECIST 1.1 and iRECIST in Solid Tumor Clinical Studies |
Xiangchen (Bob) Cui,
Sri Pavan Vemuri |
source |
24 |
| PHUSE US |
2020 |
Get in Your Lane! Building Swimmer Plots Using SAS 9.4 [poster] |
Kristi Garner,
Sri Talluri |
source |
1 |
| PharmaSUG |
2019 |
Fine-tuning your swimmer plot: another example from oncology |
Steve Almond |
source |
25 |
| PHUSE US |
2019 |
Efficacy Endpoint Visualization of Investigational Products for Cancer Patients Using R Shiny |
Beverly Martinez,
Mukul K Mittal |
source
presentation source |
12 |
| PHUSE EU |
2018 |
Step-by-step Guide to Efficacy Analysis in Solid Tumors Oncology Clinical Trials |
Anastasiia Tiurdo |
source
presentation source |
11 |
| PharmaSUG |
2017 |
SAS Macro for Derivation of Best Overall Response per RECIST v. 1.1 |
Bob Zhong,
Jiangfan Li,
Hong Xie,
Peter De Porre,
Kenneth Maahs,
Kyounghwa Bae |
source |
9 |
| PharmaSUG |
2015 |
Two different use cases to obtain best responses using RECIST 1.1: SDTM and ADaM |
Kevin Lee,
Vikash Jain |
source |
17 |
| PHUSE EU |
2014 |
Oncology Efficacy Endpoints |
Sarah Berenbrick |
source
presentation source |
3 |
| PHUSE EU |
2013 |
Overcoming Difficulties in Implementing RECIST Criteria |
Gerlind Ruhnke |
source
presentation source |
6 |
| PharmaSUG |
2012 |
Tumor Assessment using RECIST: Behind the Scenes |
Suhas R. Sanjee,
Rajavel Ganesan,
Mary N. Varughese |
source |
7 |
| MWSUG |
2011 |
Using a Double DOW Loop to Compute Progression Free Survival |
Matthew Nizol |
|
9 |
| NESUG |
2009 |
A Proposed SDTM Implementation of Response Data for Solid Tumor Trials in Oncology |
Mei Dey,
Elisabeth Pyle |
|
18 |
| PharmaSUG |
2009 |
Are you computing Confidence Interval for binomial proportion using PROC FREQ? Be Careful!! |
Sandeep Sawant |
|
6 |
| PHUSE EU |
2008 |
RECIST Temptation |
Paul Jenkins |
source |
8 |
| PharmaSUG |
2003 |
CDISC, ADaM, and TTE: What Are These Acronyms and How Can They Help Me with My Filing? |
Sandra Minjoe,
Judy Phelps |
|
4 |
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