Time-to-event

Basic Medical Statistics Course: Module COctober 2010Wilma Heemsbergen

SPSS file: trial_rt.savInt J Radiation Oncology Biol Phys 2008; 72: 980-988.Update of Dutch Multicenter Dose-escalation Trial of Radiotherapy for Localized

Prostate Cancer.

Paste the syntax of the applied statistical procedures.

1. Construct a Kaplan Meier graph, similar to Figure 1-C.

- Generate the survival table.

- Look up: 5 y freedom from failure for both arms with standard errors.

2. Construct a similar Kaplan Meier graph for each prognostic group separately (risksf).

- Calculate the log rank statistic for each progn group separately, and an overall p value with the prognostic groups as strata.

3. - Perform a Cox regression with the variable arm.

- Perform a Cox regression with the variables arm and prognostic group.

Survival

Answers (total group)

Answers (total group)

EXP 78:5y = 60 months,estimate = 0.677, SE = 0.026

Answers (prog groups)

Answers (prog groups)

Answers (prog groups)

Answers (strata)

Answers (Cox Regression)COXREG efsh /STATUS=ffshi(1 THRU 3) /METHOD=ENTER arm /CRITERIA=PIN(.05) POUT(.10) ITERATE(20).

COXREG efsh /STATUS=ffshi(1 THRU 3) /METHOD=ENTER arm risksf /CRITERIA=PIN(.05) POUT(.10) ITERATE(20).

Syntax

Cox Regression (optional)

1. Construct the variables “death due to prostate cancer”, and “death due to other causes”.

2. Test in a univariate model whether the following factors have prognostic value (for each endpoint separately): rt dose, Gleason, T stage, baseline PSA, age, diabetes, smoking.

3. Construct a MV model with variables who have a significance level of p<0.1 in the MV model.