The table below shows 20 patients who have been diagnosed with cancer. The first column shows the follow up (in years) of the patients who were alive at review. In the second column, the follow up till time of death is indicated. The third column shows the time to last review in the patients who were lost to follow up:
| Alive (Years) | Dead (Years) | Lost to FU (Years) |
|---|---|---|
| 0.2 | 0.6 | 0.8 |
| 0.4 | 1.2 | 1.4 |
| 1.5 | 1.4 | 1.8 |
| 2.2 | 1.9 | 2.1 |
| 2.5 | 2.1 | 3.6 |
| 3.1 | 2.5 | |
| 3.5 | 3.8 | |
| 4.1 |
The data is also available in Q9.rda
- Calculate the 5-year survival in the best-case scenario, using life table analysis.
- Calculate the 5-year survival in the worst-case scenario, using life table analysis.
- Show the best-case scenario and worst-case scenario survival curves in 1 graph, using life table analysis.
- Perform the Kaplan-Meier survival analysis in the best-case scenario.
- What is the survival in Q4 at 4.1 years?
- What is the median survival in Q4?
- Perform the Kaplan-Meier survival analysis in the worst-case scenario.
- What is the survival in Q7 at 4.1 years?
- What is the median survival in Q7?
The outcome data of 20 patients who had a total ankle replacement are listed in survivalankle.rda.
- Calculate the 10-year Kaplan-Meier survival of the prosthesis using revision for aseptic loosening as ‘hard end point’.
- Calculate the 10-year Kaplan-Meier survival of the prosthesis using revision as ‘hard end point’.
- Calculate the 10-year worst-case scenario Kaplan-Meier survival of the prosthesis using revision as ‘hard end point’.
The details of 20 patients who had a total hip replacement are listed in survivalhip1.rda. Ten patients had ‘Hip1′ and ten patients ‘Hip 2′. The statistical end point was revision for any cause. Apart from the type of hip replacement, the two groups had identical treatment and were of similar composition. The patient number, follow up time (continuous), censor (dichotomous) and grouping (nominal) are indicated in the data frame.
- Plot the Kaplan-Meier survival curve of hip 1 in brown and hip 2 in blue.
- Is ‘Hip 1′ better than ‘Hip 2’? Use the log rank test, cox proportional hazards and parametric regression analysis with the “exponential” and “Weibull” distributions to substantiate your answer.