STEPS TO FOLLOW FOR THIS SURVIVAL ANALYSIS AND MARKOV COST EFFECTIVENESS CALCULATOR | ||

1. | Enter Data, Comma Delimited (on form 1, box above) Submit Data to Survival Analysis Form. | |

2. | Plot Survival Curves and Hazard Curves (on form 2). | |

3. | Calculate Transition Probabilities and Enter Costs and Utilities for Markov Analysis (on form 2). | |

4. | Submit Data to Markov Analysis and Cost Effectiveness Form (on form 3). |

**References:**

1. Dalgaard, P. Statistics and Computing: Introductory Statistics with R. Chapter 12, Survival Analysis. Springer 2002.

2. Drzewiecki, KT and Andersen, PK. Survival with Malignant Melanoma, A Regression Analysis of Prognostic Factors. Cancer. 49:2414-2419, 1982.

3. Lawless, JF. Statistical Models and Methods for Lifetime Data. 1982, John Wiley & Sons, New York.

4. Pezzullo, JC. "Cox Proportional Hazards Survival Regression." at http://statpages.org/prophaz.html.

5. Briggs A. et al. Decision Modelling for Health Economic Evaluation. Oxford University Press, 2006.

6. Bewick V. et al. Statistics Review: Survival Analysis. Critical Care. 8(5):389-394, 2004.

Survival Analysis, Proportional Hazards, Markov Analysis and Cost Effectiveness

The proportional hazards assumption is that the effect parameters (covariates) multiply hazard: for example, if taking Treatment 'X' halves your hazard at time 0, it also halves your hazard at time 1, or time 0.5, or any given time, while the baseline hazard may vary. The effect parameter(s) estimated by any proportional hazards model can be reported as hazard ratios.

If you have two separate (treatment) groups in your survival dataset, from the survival results you can then generate "transition probabilities" (and add cost and utilities per Markov cycle) and this data can be submitted in the next form which will use Markov analysis to generate and plot incremental cost effectiveness results using "Group A" as the baseline, versus "Group B". The advantage of submitting the Survival results to the Markov calculator is that you can take survival data from a 5 year study and project out to 10, 20 years (cycles), or more. For this basic calculator there are only two Markov states: "No Event" (survived) and "Event" (died).