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Delayed-entry models using PROC PHREG in Survival Analysis

Statistical Consultancy Team

Time-to-event data often arise in clinical research, and in many cases represent the primary outcome of interest. These data generally represent the elapsed time between a reference time-point (e.g., treatment randomization) and an event of interest (e.g. death, relapse, etc.).

Whereas right censoring is a feature that is easily accommodated by most existing software, the same doesn’t strictly hold for another feature of survival data, left-truncation. In this post we’ll describe what left-truncation is, when it can arise and provide some SAS code that can be used to derive survival estimates and curves. 

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Topics: Survival Analysis, Statistical Programming, SAS Programming, SAS, PROC PHREG

Prentice-Wilcoxon Test for Paired Time-to-Event Data

Statistical Consultancy Team
In survival analyses we conventionally compare a time-to-event endpoint between two or more strata; patients are either represented in one strata or the other and the strata are independent of each other.
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Topics: Survival Analysis, Statistical Programming, Statisticians in the Pharmaceutical Industry (PSI), SAS Macros, Prentice Wilcoxon Test

Survival Analysis: Lifetables and Cox Proportional Hazard Model

Clinical Programming Team

Survival models are commonly used in clinical trials as they are designed to perform 'time to event' analyzes on data with censored observations – something that probably all clinical programmers are familiar with. As censored observation in this case we understand a subject who did not experience the defined event during the whole observation period.

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Topics: Survival Analysis, Adverse Events (AEs), Clinical Programming, Cox Proportional Hazard Model

Bayesian Methods and a review of the European Statistical Forum

Statistical Consultancy Team

A member of Quanticate's Statistical Consultancy Team writes about their attentedence and presentation at the European Statistical Forum, Milan Nov, 2011.

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Topics: Regulatory Requirements, Bayesian Statistics, Bayesian Study Design, European Statistical Forum, Bayesian Methods, Survival Analysis, Interim Analysis, Biostatistics Consulting, Clinical Trial Phases

Survival Analysis in Medical Research and Bayesian Methods

Statistical Consultancy Team

We are pleased to confirm that Quanticate will have a speaker at the 2011 European Statistical Forum (ESF) Conference. Entitled “Bayesian Study Design for Survival Endpoints: Enhancing decision making in early clinical development”, the talk will focus on Phase II, or ‘Proof of Concept’ studies.

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Topics: Bayesian Statistics, Bayesian Study Design, European Statistical Forum, Bayesian Methods, Survival Analysis

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