What is the adjusted hazard ratio and its associated 99% confidence interval for a patient with CD4 count 400 v.s. a patient with CD4 count 300? Interpret your result.R语言解决

To calculate the adjusted hazard ratio and its associated 99% confidence interval for a patient with CD4 count 400 vs. a patient with CD4 count 300, we need to perform a survival analysis using a Cox proportional hazards model. Here is an example code in R:

# Load the survival package
library(survival)

# Import the data
data <- read.csv("data.csv")

# Fit a Cox proportional hazards model
model <- coxph(Surv(time, status) ~ cd4_count, data=data)

# Calculate the adjusted hazard ratio and its associated 99% confidence interval
HR <- exp(coef(model))
conf.int <- exp(confint(model, level=0.99))

# Print the results
cat("Adjusted hazard ratio:", HR, "\n")
cat("99% confidence interval:", conf.int, "\n")

Assuming that "cd4_count" is the variable representing the CD4 count in the dataset, the above code will fit a Cox proportional hazards model to the data and calculate the adjusted hazard ratio and its associated 99% confidence interval for a patient with CD4 count 400 vs. a patient with CD4 count 300.

The interpretation of the result is as follows: If all other variables in the model are held constant, a patient with CD4 count 400 has a HR times higher (or lower, depending on the sign of the coefficient) risk of the event of interest (e.g., death or disease progression) compared to a patient with CD4 count 300. The 99% confidence interval provides a range of values within which we can be 99% confident that the true HR lies.