Related Experiment Video
Updated: Jul 18, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
The estimand framework had implications in time to patient-reported outcomes deterioration analyses in cancer
Francesco Cottone1, Fabio Efficace2, David Cella3
1Data Center and Health Outcomes Research Unit, Italian Group for Adult Hematologic Diseases (GIMEMA), Rome, Italy.
Objectives:
To apply the estimand framework in time to deterioration (TTD) analysis of patient-reported outcomes (PROs), and identify the appropriate statistical methods to deal with intercurrent event (IEs) such as death.
Study Design And Setting:
Data from phase II randomized trial were used. We estimated TTD using European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30 questionnaire with death as the IE, by applying Kaplan-Meier (K.M.) estimator and Cox proportional hazards (PH) model. The Fine-Gray approach was explored, accounting for death as a competing risk. The estimands targeted by the aforementioned methods were defined.
Results:
We analyzed the data of 64 patients with available questionnaires at baseline. The most notable differences in TTD estimates were observed for deterioration in physical functioning: the hazard ratios were 0.44 [95% CI 0.22-0.90] and 0.62 [95% CI 0.36-1.07] by either ignoring death (31 events) or considering it as deterioration (58 events), respectively (Cox-PH model). When considering death as a competing event (Fine-Gray model), the sub-HRs was 0.51 [95% CI 0.26-1.01].
Conclusion:
Depending on the proportion and distribution of deaths occurring before deterioration between arms, the Fine-Gray competing risks model should be considered rather than KM estimator and Cox PH model to reflect the patient's experience of the disease and treatment burden.
More Related Videos
09:44Pretargeted Radioimmunotherapy Based on the Inverse Electron Demand Diels-Alder Reaction
Published on: January 29, 2019
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Related Concept Videos
Cancer Survival Analysis
Kaplan-Meier Approach
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Comparing the Survival Analysis of Two or More Groups
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Assumptions of Survival Analysis