Overview

The ASPREE Longitudinal data set contains analytical data collected for the parent ASPREE clinical trial between March 2010 and June 2017.

NOTE: Sub-study data is not included in this data set. For more information on ASPREE sub-studies please see here.

ASPREE Longitudinal Data Set Structure

The ASPREE Longitudinal Data Set has been separated into nine Sections (A-I) as seen in Table 1 below and on the panel to the left.

Table 1. Structure of the ASPREE Longitudinal Data Set.

Section Details
Section A A.1 Baseline participant demographics
A.2 Baseline and longitudinal clinical information
Section B B.1 Baseline past medical and cancer history
B.2 Baseline and longitudinal physical examination
B.3 Longitudinal cancer screening
B.4 Longitudinal pathology
B.5 Longitudinal concomitant medication use
B.6 Longitudinal family medical history
B.7 Non-prescription medication use (Milestone visit only)
Section C C.1 3MS examination
C.2 Longitudinal COWAT, HVLT-R, SDMT
Section D D.1 Longitudinal physical function
Section E E.1 Longitudinal Life Disability
E.2 Longitudinal CES-D 10
E.3 Longitudinal SF-12
Section F F.1 Primary and secondary endpoint data from 2018 New England Journal of Medicine papers
F.2 All reported endpoints
F.3 Adjudicated secondary endpoints
F.4 Hospitalisation for reasons other than endpoints
Section G G.1 Study medication data
G.2 Study medication (Milestone questionnaire)
Section H H.1 Visit completion
Section I I.1 Baseline derived variables

To see more information about particular sections, please click on the section you are interested in on the panel to the left.

Quality Control

ASPREE Web Accessible Relational Database (AWARD)

AWARD-Data supported data entry of study measures and events, participant booking, communication between study staff and GPs, study medication tracking and upload of supporting documentation for events. Each structured data field was subject to pre-programmed value ranges, process prompts and protocol compliance checks at the point of data entry, with the aim of preventing transcription errors in real time. Staff were alerted to any out-of-range or missing values when data were saved, and prompted to double check that these data were correct. For more information on the AWARD suite please see the Data Collection section.

A pop-up web warning for an out of range Urine Albumin:Creatinine ratio.

In addition to pop-up warnings, page submission restrictions were introduced. Each Electronic Case Report form (eCRF) included a ‘save draft’ and ‘submit’ button. The ‘save draft’ allowed staff to enter pieces of data without restrictions. However, when the ‘submit’ option was utilised the completeness of data entry was confirmed by the web-portal according to pre-specified validation rules. If a mandatory field was missed a red error message appeared to alert staff (see Figure 2).

Web restriction for missing data.

Throughout longitudinal data collection, eCRFs with a status of ‘Draft’ or ‘Not Entered’ appeared on a list of visits with missing data. This list was available through the web portal to all staff and was supervised by site managers. Visits were removed from the list only when all data was entered.

Annual visit showing ‘Draft’ and ‘Not Entered’ eCRF status.

Wherever possible, staff entered raw data via the web application (e.g. individual blood pressure readings) and AWARD was programmed to calculate additional variables from the raw data (e.g. mean blood pressure). To aid the timely completion of study activity, AWARD also supported complex operational tasks such as visit bookings.

In ASPREE, clinical event data were manually abstracted from clinical records. To minimise the need for interpretation by data collectors, clinical event record forms prompted staff to transcribe key elements that comprised the event definition, rather than to interpret clinical information and record outcomes. Logic checks, particularly related to illogical dates, were implemented to screen for transcription errors. To ensure correctness, primary and secondary endpoints were adjudicated by at least two clinical experts based on raw transcribed data and PDF copies of clinical records.

Randomisation Restrictions

Protocol deviations were minimised through the introduction of web-based randomisation restrictions. Staff were unable to randomise participants with ineligible data, for example low haemoglobin, abnormal blood pressure, history of bleeding ulcer or ineligible date of birth.

Data Queries

All data included in the ASPREE Longitudinal data set were queried for missing and out-of-range values. Ranges for individual values were determined by the ASPREE International Data Management Committee (IDMC). Changes in values between visits were considered out of range if the change fell outside three standard deviations from the mean change in values between baseline test values and the next administration of the test. Automated querying of data for missing or out of range values produced an “Action List” of outstanding activity for each staff member. Actions were resolved either by updating the data entered or providing an explanatory response (commentary code) on the action list (e.g. data missing due to measurement device error). Data that were confirmed to be correct according to source documentation but considered to be unlikely or improbable, were reviewed and adjudicated by the IDMC. Data adjudicated as implausible (outside the possible range for humans) were removed and considered to be missing due to staff error at the time of data collection.

Commentary Values

Interpretation of ASPREE data cannot be undertaken without consideration of the data collection and data querying processes. To ensure that the data is analysed in the context intended by the investigators, all data fields have been annotated with a commentary code. The commentary codes provide explanation with regard to missing data, out of range data, alterations to data collection methods and other special considerations.

Staff Training and Monitoring

All staff were required to attend an initial training session covering good research practice, clinical research ethics and relevant Standard Operating Procedures (SOPs) that described all study procedures.

Visit Monitoring

Each staff member involved in visit conduct activity had two to four visits (minimum of two) assessed each year by a designated monitor. Monitors assessed staff for their adherence to protocol and compliance with visit conduct SOPs, reviewing areas such as adherence to compulsory scripts, following predetermined test administration sequences and timings, collection of endpoint related information and accuracy of questionnaire administrations.

File Monitoring

A designated file monitor reviewed the data collection processes by checking the source documents of five participant files per staff member every year. Source documents were assessed for completeness (including both data and ‘office use’ fields), and transcription accuracy compared to the entry of the corresponding eCRF on the web portal.

Online Monitoring

As discussed above, AWARD-Data was designed to internally monitor many aspects of data entry.

Site Monitoring

All sites are monitored annually by trained clinical research site monitors following Good Clinical Practice guidelines. Sites were assessed for adherence to standardised operating procedures for drug log management, report production, ethics approvals, regulatory documents, work practices, equipment management and communication.