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Review
. 2003 Jul 21;89(2):232-8.
doi: 10.1038/sj.bjc.6601118.

Survival analysis part I: basic concepts and first analyses

T G Clark  1 , M J Bradburn, S B Love, D G Altman
Affiliations
Review

Survival analysis part I: basic concepts and first analyses

T G Clark et al. Br J Cancer. .
No abstract available

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Figures

Figure 1
Figure 1
Converting calendar time in the ovarian cancer study to a survival analysis format. Dashed vertical line is the date of the last follow-up, R=relapse, D=death from ovarian cancer, Do=death from other cause, A=attended last clinic visit (alive), L=loss to follow-up, X=death, □=censored.
Figure 2
Figure 2
Relapse-free survival curves for the lung cancer trial. * Median relapse-free survival time for each arm, + censoring times, CAP=cytoxan, doxorubicin and platinum-based chemotherapy.
Figure 3
Figure 3
Survival and cumulative hazard curves with 95% CIs for the ovarian cancer study. Std.Err=standard error. (A) Kaplan–Meier survivor function, (B) cumulative incidence curve, (C) cumulative hazard function, (D) hazard function (smoothed).
Figure 4
Figure 4
Relationships between (parametric) hazard and survival curves: (a) constant hazard (e.g. healthy persons), (b) increasing Weibull (e.g. leukaemia patients), (c) decreasing Weibull (e.g. patients recovering from surgery), (d) increasing and then decreasing log-normal (e.g. tuberculosis patients).
Figure 5
Figure 5
FIGO stage and prognosis in the ovarian study. Chisq=χ2.
See this image and copyright information in PMC

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References

    1. Altman DG (2003) Practical statistics for medical research. London: Chapman & Hall
    1. Altman DG, Bland JM (2003) Statistics notes: interaction revisited: the difference between two estimates. BMJ 326: 219. - PMC - PubMed
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    1. Clark TG, Stewart ME, Altman DG, Gabra H, Smyth J (2001) A prognostic model for ovarian cancer. Br J Cancer 85: 944–952 - PMC - PubMed
    1. Collett D (1994) Modelling Survival Data in Medical Research. London: Chapman & Hall

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