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Case Study in Parametric Survival Modeling and Model Approximation

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Abstract

Consider the random sample of 1000 patients from the SUPPORT study, 352 described in Section 3.12 In this case study we develop a parametric survival time model (accelerated failure time model) for time until death for the acute disease subset of SUPPORT (acute respiratory failure, multiple organ system failure, coma). We eliminate the chronic disease categories because the shapes of the survival curves are different between acute and chronic disease categories. To fit both acute and chronic disease classes would require a log-normal model with σ parameter that is disease-specific.

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References

  1. W. A. Knaus, F. E. Harrell, J. Lynn, L. Goldman, R. S. Phillips, A. F. Connors, N. V. Dawson, W. J. Fulkerson, R. M. Califf, N. Desbiens, P. Layde, R. K. Oye, P. E. Bellamy, R. B. Hakim, and D. P. Wagner. The SUPPORT prognostic model: Objective estimates of survival for seriously ill hospitalized adults. Ann Int Med, 122:191–203, 1995.

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  2. C. Kooperberg, C. J. Stone, and Y. K. Truong. Hazard regression. J Am Stat Assoc, 90:78–94, 1995.

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Harrell, F.E. (2015). Case Study in Parametric Survival Modeling and Model Approximation. In: Regression Modeling Strategies. Springer Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-19425-7_19

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