**Help Aids **Top

**Application: **The
determination of the number of patients needed in a prospective comparison of
survival curves, when the control group patients have already been followed for
some period, following hypotheses are usually used:

**Procedure**:

- Enter

a) value of α, the probability of type I error

b) value of β, the probability of type II error, or (1-power) of the test

c) value of δ, the minimum hazards ratio, it is specified in alternate hypothesis

d) value of M_{S}, the control median survival (year), it is estimated
from existing control data

e) value of Q_{C}, the **proportion of patient in control group compared with
experimental group**

f)
value
of Q_{E},
the **proportion of patient in experimental
group compared with control group, where Q _{C} + Q_{E} = 1**

g) value of T_{0}, **accrual duration (year), the length of time to recruit patients for
study.**

**h) value of **T-T_{0}, **follow-up
duration (year), the length of study time of all recruited patients to the end
of study T**

- Click the button “Calculate” to obtain the sample size of patients in the experimental arm and the total number of deaths at the end of study

**Assumption:**

1.
Time
to survival is exponential distributed with hazard rate λ.

**Formula:**

Consider
that there are two independent groups of sizes *n _{C}*
and

Under
null hypothesis,, test statistic is, whereandare the estimated hazard rates, , and

For the
determination of sample size and power one specified the minimal relevant difference, which yield. Under the null hypothesis,and where. is defined as

The
sample size to achieve specified significance level and power is, whereis the upper 100(1-p) percentile
of the standard normal distribution.

Here the calculator uses two-sided test. α of the above equation is replaced by α/2.

** **

**Notations:**

**α****:** The
probability of type I error (significance level) is the *probability of rejecting the true null
hypothesis. *

**β****:** The
probability of type II error (1 – power of the test) is the *probability of
not rejecting the false null hypothesis.*

**Example:**

Consider that a clinical trial is to be
conducted for a disease with moderate levels of mortality with hazard rare
λ=0.30, yielding 50% survivors after 2.3 years (*M _{S}*=2.3). Suppose that with treatment we are interested in a reduction in
hazard to

**Reference**: Lachin (1981) *Controlled Clinical Trials* 2: 93-113