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overall survival

69 papers and 2 presentations; 70 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2026 Linear versus Log-Log Confidence Intervals for Kaplan-Meier Survival Estimates: Statistical Rationale and Practical Implementation using SAS 9.4 Prayag Shah source 8
PharmaSUG 2026 Oncology Solid Tumor Subcutaneous vs Intravenous Late-stage Study Analysis Sumanjali Mangalarapu,
Chuqing Chen,
Anilkumar Anksapur		 source 11
PHUSE US 2026 Group, Collapse, Repeat: A Dynamic SAS Macro for Stratification Pooling in Oncology Efficacy Analysis Venkatesh Burla source
presentation source		 9
PHUSE US 2026 Interactive and Instant: GenAI-Driven Creation of Clinical Trial Applications Marcin Dubel source
presentation source		 12
PHUSE US 2026 Mapping Minimal Residual Disease (MRD) Biomarker Data in Hematologic Malignancies: Clinical Significance and Data Standards in SDTM and ADaM Jyothi Nelakurthi source
presentation source		 8
PHUSE US 2026 Practical Survival Analysis Techniques for Clinical Trials Using SAS Xue Ding,
Tianchen Xu		 source
presentation source		 10
PHUSE APAC 2026 Illustrating treatment switching using Rank preserving structural failure time model in Oncology study Swarupa Changan source
presentation source		 11
PharmaSUG 2025 ADaM Pet Peeves: Things Programmers Do That Make Us Crazy Sandra Minjoe,
Nancy Brucken		 source 13
PharmaSUG 2025 Implementation of the inverse probability of censoring weighting (IPCW) Model in Oncology Trials Mei Huang,
Shibani Harite,
Haijun Ma,
Linsong (Athena) Zhang		 source 17
PharmaSUG 2025 Mastering the Maze of Oncology Endpoints: A Unified SAS Approach for Randomized Controlled Trial Analysis Yuxin Wang,
Kelly Chao,
Wenqing Yu,
Hongbing Jin		 source 11
PharmaSUG 2025 Sensitivity Analysis for Overall Survival Binal Mehta,
Patel Mukesh		 source 13
PharmaSUG 2025 Visually Exploring Kaplan-Meier Curves Using SAS GTL and R survminer Yang Gao source 5
PHUSE US 2025 An Intuitive Way to Derive the Last Known Alive Date in R Marckenley Mercie,
Diana Tai		 source
presentation source		 12
PHUSE US 2025 Revolutionising Cancer Trials with Adaptive Designs and Bayesian Analysis Navneet Jha source
presentation source		 11
PHUSE US 2025 SAS Programming approach for adjustment of treatment switching using Two-Stage Method Mani Mudumba source
presentation source		 13
PharmaSUG 2024 Oncology ADaM Datasets Creation Using R Programming: A Comprehensive Approach Ishwar Chouhan source 29
PharmaSUG 2024 Programming Considerations in Deriving Progression-Free Survival on Next-Line Therapy (PFS2) Alec McConnell,
Yun Peng		 source 5
PHUSE US 2024 Comparison of Standard Log-Rank Test with Selected Alternatives Elena Valkanova,
Bulat Fatykhov		 source
poster source		 18
PHUSE EU 2023 Efficacy Endpoints in Adjuvant and Neo-Adjuvant Oncology Trials Yuliia (Piddubna) Cherednichenko,
Anna Amosova		 source
presentation source		 15
PHUSE EU 2023 Real-World Outcomes and Biomarker Testing in Cancer Patients: Exploration of a Novel Genetic Database from Routine Clinical Practice in England Alexandrina Lambova,
Fiona Ingleby		 source
presentation source		 5
PharmaSUG 2023 Guidelines for the Statistical Analysis in German Dossier Submissions Meiling Gao,
Xi Qian,
Hui Mao		 source 8
PharmaSUG 2023 Survival Methods for Crossover in Oncology Trials Brian Mosier source 18
PHUSE US 2022 Jumping on the Real-world Data (RWD)/Real-world Evidence (RWE) Bandwagon? A Guide for Statistical Programmers to Understand Payer Claims Data [presentation] Rachana Agarwal source
video		 13
PHUSE EU 2021 Statistical Training for Health Technology Assessment Statistical Programmers Anastasia Kokoreva,
William Malbecq		 source
video
presentation source		 7
PHUSE EU 2021 Using R - TFL Generation with Custom Functions [poster] Jem Chang,
Vikram Kasarala		 source
video		 1
PharmaSUG 2020 %MVMODELS: a Macro for Survival and Logistic Analysis Jeffrey P. Meyers source 23
PHUSE US 2020 CDISC's ADTTE Domain: Time-to-Event Analysis From a Programmer's Point of View Frieder Wolff,
Vitali Gering		 source
poster source		 8
PHUSE US 2020 Data Standards Used for Electronic Submission of Real-World Evidence in New Drug Application (NDA) Nicole Thorne,
Kathy Wu		 source
presentation source		 10
PHUSE US 2020 Let Us Trace Back to the Beginning from the End Madhusudhan Reddy Papasani,
Swathi Kotla		 source
presentation source		 12
PHUSE EU 2019 Don't Dream It, Be It Harnessing SAS GTL to Produce Customized Composite Graphics Neville Cope source
presentation source		 10
PharmaSUG 2019 F2Plots: Visualizing relative treatment effects in cancer clinical trials Yellareddy Badduri source 9
PharmaSUG 2019 Framework for German Dossier Submissions Kriss Harris source 8
PharmaSUG 2019 Jump Start your Oncology knowledge Xiaoyin Zhong,
Feng Liu		 source 9
PharmaSUG 2019 Learning SAS GTL Basics with Practical Examples Jinit Mistry source 12
PharmaSUG 2019 Useful SAS techniques in Efficacy Analysis for Oncology studies Joy Zeng source 21
PharmaSUG 2019 Visualize Overall Survival and Progression Free Survival at the Same Time! Kriss Harris source 2
SGF 2019 Framework for German Dossier Submissions Kriss Harris source 9
SGF 2019 Using SAS Macros to Analyze Lifetime Data with Left Truncation Zhen-Huan Hu source 11
PHUSE US 2019 Dashboarding Analytics for Oncology Endpoint Data Using SAS Vidya Muthukumar source
presentation source		 7
PHUSE US 2019 Misuse and Misapplication in Statistical Data Analysis - A Topic that Never Goes Out of Style Corinna Miede source
presentation source		 12
PHUSE US 2019 The Power of Sharing Clinical Data: Real Projects with Real Impacts David Handelsman source
presentation source		 6
PHUSE EU 2018 Forest Plots in Survival Subgroup Analyses Michael Brockmann,
Julia Benzing		 source
presentation source		 11
PHUSE EU 2018 Implementation of Data Cut Off in Analysis of Clinical Trials Ann Croft source
presentation source		 13
PHUSE EU 2018 Methods for Survival Analysis with Competing Risks Laura Marquis,
Leonie Wagner		 source
presentation source		 8
PHUSE US 2018 Unleashing Potential of Graphs for Oncology Trials Manoj Pandey source
presentation source		 12
PharmaSUG 2018 ADINTDT and ADTTE for Survival Sweep in Oncology Studies Christine S Teng,
Wenyu Hu		 source 6
PharmaSUG 2018 Family of PARAM***: PARAM, PARAMCD, PARAMN, PARCATy(N), PARAMTYPE Kamleshkumar Patel source 12
PharmaSUG 2018 Implementation of Data Cut Off in Analysis of Clinical Trials Mei Dey source 15
PharmaSUG 2018 Implementing the Rank-Preserving Structural Failure Time Model in SAS and R Bradford J. Danner,
Indrani Sarkar		 source 8
PharmaSUG 2018 Sense and Censorability: Learn censoring techniques with ADTTE for your survival Shilpakala Vasudevan source 12
PHUSE EU 2016 Considerations in the Use of Propensity Scoresin Observational Studies Lawrence Rasouliyan,
Estel Plana		 source
presentation source		 17
PharmaSUG 2016 Programming Support for Exposure-Response Analysis in Oncology Drug Development Peter Lu,
Hong Yan		 source 8
PharmaSUG CN 2015 Survival Plots using SAS PROC LIFETEST, GPLOT, and SGPLOT: What are their difference? Ka Chun Chong,
Benny Chung-Ying Zee		 8
SGF 2015 A Set of SAS Macros for Generating Survival Analysis Reports for Lifetime Data with or without Competing Risks Zhen-Huan Hu source
zip		 6
SGF 2015 Kaplan-Meier Survival Plotting Macro %NEWSURV Jeffrey P. Meyers source 20
PHUSE EU 2014 Checking Symmetry in Predefined Time Assessments Antonio Nieto,
José Luis Jiménez Moro		 source
presentation source		 9
PHUSE EU 2014 Evaluating the Tradeoff between Quality of Life through Quality-Adjusted Survival Analysis Lawrence Rasouliyan source
presentation source		 12
PHUSE EU 2014 Inverse Probability of Censoring Weighting for Selective Crossover in Oncology Clinical Trials José Luis Jiménez Moro,
Javier Gómez Garcia		 source
presentation source		 5
MWSUG 2014 Kaplan-Meier Survival Plotting Macro %NEWSURV Jeffrey P. Meyers 20
PharmaSUG CN 2014 Design and Construct Efficacy Analysis Datasets in Later Phase Oncology Study Huadan Li,
Changhong Shi		 9
PharmaSUG 2014 Kaplan-Meier Survival Plotting Macro %NEWSURV Jeffrey P. Meyers source 19
PharmaSUG 2014 Standardization of Confidence Intervals in PFS Tables - a Macro Approach John Saida Shaik,
Boxun Zhang		 source 4
PHUSE EU 2013 Efficacy Endpoints in Oncology Angelo Tinazzi source 9
PHUSE EU 2013 Oncology Endpoints: An Unexpected Journey Waseem Jugon,
Mijanur Rahman		 source 12
PHUSE EU 2012 Bootstrap simulations to estimate Overall Survival based on the distribution of a historical control Antonio Nieto,
Javier Gómez		 source
presentation source		 7
WUSS 2010 Survival 101: Reporting Survival Curves Using Sample Data from the Colorectal Cancer Outcomes Database Anna ter Veer source 11
WUSS 2008 Surviving Left Truncation Using PROC PHREG Aimee Foreman,
Ginny Lai,
Dave P. Miller		 source 8
PHUSE EU 2008 RECIST Temptation Paul Jenkins source 8
MWSUG 2008 Creating Macros for Survival Data in Oncology Study Jagannath Ghosh 8
PharmaSUG 2007 %SurvTab: A SAS Macro to Make Survival Analysis Easier Yinmei Zhou,
St. Jude Children's		 15
SEUGI 1997 %SUPLANA - a powerful SAS macro routine for survival analysis Angelo Tinazzi,
Valter Torri		 source 6

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