In this trial, there are various statistical techniques used to analyse

data in order to determine if result of these test were statistically

significant. Consequently, this allows us to identify if we can be confident

enough to apply the results to patient groups suffering from CLL and SLL

outside of this study.

Group

sequential testing provides us with a stopping criterion to evaluate whether we

accept or reject the null hypothesis at each interim stage with conclusive

evidence of the efficacy of the treatment. In this test, the initial sample

size is not fixed, which is useful as there are new cohorts of patients

entering the trial at different points. As there are multiple analysis to be

made, the p value needs to be altered for each analysis to avoid inflating Type

1 error. This allows trials to either be stopped early or allows patients transfer

into the control group. These decisions are made during interim analysis (Chen et al., 2017).

The purpose of interim

analysis is to analyse data before the completion of the data collection occurs

in the study. This is useful to researchers as it is often the case that clinical trials

enroll patients in a staggered manner as it is continuous. As a result, they

are able to use the data that has been collected so far to assess the

difference between the treatment group and the placebo group. This in turn,

allows an early termination or changing of the study based on whether there are

beneficial or harmful factors identified post analysis (Chakraborty and Kumar, 2016).

The hazard ratio measures the

effect of an intervention on an outcome over a period of time. In this case the

hazard ratio was used to measure the effect of Ibrutinib group compared to the

treatment group and the outcome was progression free survival. The ratio can be

defined as Hazard in the Ibrutinib group/hazard in the placebo group. In the interim

analysis, the hazard ratio was 0.203 and this means that 20% of patients were

more likely to experience PFS compared to the placebo group (Sedgwick and Joekes, 2015).

Kaplan Meir method is used

when there are incomplete observations in cases where a patient discontinues or

if they joined the study later. Therefore, having shorter observation time and

so may or may not experience the event within the follow-up time. We cannot

exclude these subjects otherwise our sample size will be too small. (Kishore et al., 2010). Therefore,

Kaplan Meir method is used to estimate survival over time in spite of these

issues. At each interval, a survival probability was calculated. After the

first interval, 91% of the treatment group did not experience PFS. The two

curves can be compared to see if the results are statistically significant and

this is done by long Rank test. In the log rank test, we generate a chi-squared

value. The p-value was 0.0001 > 0.05, therefore there is a significant

difference between the survival times of both groups (Rich et al., 2010).

The exposure

adjusted incidence rate (EAIR) can be calculated by dividing the total number

of subjects experiencing a specific event by the time under which the patient

was exposed to risk (Liu et al., 2006) (Siddiqui, 2009). In relation to the

Helios trial, the EAIR can be applied to adverse events for example, major

haemorrhage can be used to see whether the treatment was effective or not over

different durations. The researchers found that 11 patients in the ibrutinib

group suffered from a haemorrhage following a median duration of 4.21 months

(EAIR= 2.61). In the placebo group, there were 5 patients who experienced the

same event in a median duration of 2.3 months (EAIR=2.17); thereby,

highlighting the higher incidence rate of a haemorrhage following ibrutinib

treatment.

In efficacy

analysis when there are issues with the compliance of treatment, the results

obtained from those who have followed protocols are analysed in order to

determine whether the experimental therapy is better suited than current/alternative

therapies. The trial also utilised intention-to-treat analysis as a basis for

the efficacy analysis. This is based upon the theory that all patients should

be put into randomly allocated groups regardless of which experimental group

they were initially assigned to or whether they the complete the treatment

(Sphweb.bumc.bu.edu, 2016). Due to compliance issues to the protocols the

efficacy analysis for ibrutinib was required. The sample for the analysis

excludes those who did not follow the regime, patients that were lost via

sample attrition and patients from the crossover group. However, an issue

arises due to the smaller sample size attained for the efficacy analysis. As a

result, the comparison drawn between the ibrutinib treatment and current therapy

is less representative when generalised to the population.

The Inverse

probability of censoring weighting (IPCW) is used to assess the clinical

benefit of the experimental and control groups. It attempts to reduce bias

caused by treatment change. It was used to ensure that the outcome of the study

was not affected by crossing over. For example, if a patient in the control

group was experiencing symptoms of relapse, then the patient was crossed over

to the treatment group (90 patients crossed over). This allowed for the

patient’s interests to be put above the studies interests. The patients that were

crossed over were weighted zero and those who remained in the placebo group

were given a higher weighting. It was assumed that there were no measures of

confounding variables and that randomisation was not preserved (Ascopubs.org,

2017)

The

Fisher Exact Test was used to analyse negative response to Minimal Residual

Disease (MRD). This allowed us to see whether there was an association between

experiencing negative MRD and receiving Ibrutinib. It uses contingency table to display the probability of different outcomes. The

rows were the outcome and the column is the exposure. The data in the contingency table was entered into the

SAS programmed and a p-value was generated (Biostathandbook.com,

2017).