Related Experiment Video
Updated: May 11, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Biostatistics primer: what a clinician ought to know--prognostic and predictive factors
Lorinda Simms1, Helen Barraclough, Ramaswamy Govindan
1Statistics and Information Sciences, Eli Lilly and Company, Toronto, Ontario, Canada.
Abstract:
Several prognostic factors in oncology have been established over the years, such as performance status, tumor size, and disease stage. The identification of prognostic and predictive factors is becoming increasingly important in medical research, particularly as scientific discoveries have led to better understanding of diseases and genetics, resulting in tailored therapy. Advances in drug discovery and better understanding of the mechanism of action, may also identify factors that may be prognostic and/or predictive. Prognostic or predictive factors may include patient characteristics such as age, ethnicity, sex, or smoking status, disease characteristics such as disease stage or nodal status, and molecular markers such as HER2 amplification and K ras mutation.It can be challenging to distinguish whether a factor is prognostic or predictive, based on what is reported in the literature. This article is intended to help the reader assess whether a factor is prognostic and/or predictive.
Related Concept Videos
Biostatistics: Overview
Discrete variables are...
Overview of Biostatistics in Health Sciences
Cancer Survival Analysis
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, controlled...
Statistical Software for Data Analysis and Clinical Trials
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...