Survival Analysis Biomedical Applications. Halifax SAS User Group April 29/2011. Why do Survival Analysis. Aims : How does the risk of event occurrence vary with time? How does the distribution across states change with time?
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Halifax SAS User Group
-Time from onset of cancer to death/remission
-Time from implant of pacemaker to lead survival
- recruitment in study
- onset of cancer
- insertion of Pacemaker
ex. Flu strain
ex. Type of treatment
title 'Adjusted Survival Curve by Gender';
axis1 label=('Years') order=(0 to 12 by 1);
axis2 label=(angle=90 'Proportion Surviving');* order=(0.6 to 1.0 by 0.1);
plot surv*time=gender / haxis=axis1 vaxis=axis2 legend=legend1;
%survplot (DATA=xxx_aug , TIME=time_death ,
EVENT=death ,CEN_VL=0, CLASS=event_anyshock ,
TESTOP=1, CLASSFT=cchrl , CMARKS=0, PLOTOP=0 , PRINTOP= 0,
POINTS='1 2 5 10' , SCOLOR=black, XDIVISOR=1, LABELS= ,
LABCOL=black, BY= , WHERE= , LEGEND=1 , YAXIS=2, XAXIS=1,
XMAX=15 , LCOL=black red blue, PERCENT=0, FONT=SWISS,
F1=3, F2=3, F3=3, F4=3, PLOTNAME= , ANNOTATE= , RTFEXCL=0,POPTIONS=);
Survplot Macro: Created by Ryan Lennon. 2009 Mayo Clinic College of Medicine.
The estimated probability that a patient will survive for 365 days or more is 0.56
Hazard Ratio: Ratio of estimated hazard for those with Diabetes to those without (controlling for other variables) = 0.250
The hazard of death for those with diabetes is 25% of the hazard for those without
“ The treatment will cause the patient to progress more quickly, and that a treated patient who has not yet progressed by a certain time has twice the chance of having progressed at the next point in time compared with someone in the control group.”
What are hazard ratios?. Duerden, M. What is series by Hayward Group Ltd, 2009.
1. Time dependant covariates
Comparison of 2 Methods for Calculating Adjusted Survival Curves from Proportional Hazard models. Ghali, W.A., Quan, H., Brant, R., et al. JAMA. 2001; 286(12):1494-1497.
A SAS Macro for Estimation of Direct Adjusted Survival Curves Based on A Stratified Cox Regression Model. Zhang, X., Loberiza, F.R., Klein, J.P. and Zhang, M-J.
Shunt Failure NESUG 2008. Williams, C.
Other CauseCompeting Risks Models
Rosthoj, S., Anderson, P. and Adildstrom, S. SAS macros for estimation of the cumulative incidence functions based on a Cox regression model for competing risks survival data. Computer Methods and Programs in Biomedicine, (2004) 74,69-75.