Data Management considerations in Observational studies

Preparing to load PDF file. please wait...

0 of 0
Data Management considerations in Observational studies

Transcript Of Data Management considerations in Observational studies

Data Management considerations in Observational studies
Valerie Alward, Manager RWLPR Data Management Zia Haque, Senior Director RWLPR Data Management
© Copyright 2015 Quintiles

Your Presenters
Valerie Alward Manager, Clinical Data Management, Real-World Late Phase at Quintiles Valerie Alward has been with Quintiles Real-World Late Phase Research DM group for a little over 2 years and has been a Data Team Lead for many studies. Prior to Quintiles, Valerie worked at a senior level in Data Management for several companies, including CROs and Pharmaceutical companies. Valerie started her career in clinical research in 1996 as a site coordinator and then moved on to the data management field in 1998. She has both a Masters in Management from Rensselaer University and a BA in Psychology from North Carolina State University.

Zia Haque Senior Director of Data Management, Real-World Late Phase Research Zia has been with Quintiles Real World and Late Phase (RWLPR) DM Management team since the past three years. He has worked in clinical data management for 18 years in roles of increasing responsibility and has led global DM teams in early and late phase arenas. Zia holds a BS in Chemistry & Zoology from Bangalore University, a MA in English from Karnatak University and is completing a MS in clinical research from Campbell University.

Quintiles Confidential


Today’s Webinar Audience


11.0% 12.0%

13.0% 5.0% 6.0% 2.0%2.0%


Academia Biostatistician Clinical Operations Epidemiology Health Economics/ Health Outcomes Market Access Medical Affairs Risk Management Other


Polling Questions
A small number of
? polling questions have
been added to today’s webinar to make the session more interactive

Research Study Designs Types of Late Phase studies Data Management strategies on Observational studies Q&A

Typical Hierarchy of Research Designs


* Randomized Controlled Trials

Prospective Observational Cohort Studies & Pragmatic

Case-control studies


Expert opinion

Commercial Product Continuum

Interventional Studies, Observational Studies &



Preclinical R & D

Clinical Development

Phase I

Phase II Phase III

Regulatory Submission


Observational Studies for Pre-launch Market Insight

Post-launch Observational Studies

Provide real-world data on:
• natural history of disease • burden of illness • treatment patterns • disease management
to inform development, launch strategy, and market access (product not included).

Provide real-world data on:
• pharmaceutical use (on/off-label) • safety • effectiveness • compliance, adherence, persistence • treatment satisfaction
• competitor brands • comparative effectiveness
• disease management to inform treatment use.


RCTs cannot answer all research questions
• Hypothesis - driven nature of experimental design requires substantial knowledge at the study outset and limits the potential for discovering new information
• Atypical behavior, patients, and settings – Protocol-driven behavior in highly selective patients – May not be usual physician or usual practice – Optimal patients should have best outcomes
• Do not give insights into why patients and/or clinicians use products as they do or about off-label or risky situations
• Also – Can be hard to recruit patients – May be small, with imprecise results – Intermediate endpoints may not be clinically meaningful

Types of Late Phase Studies
Interventional late phase studies
Allow for combining generalizability of Observational studies with the validity of RCTs
Non-interventional (Observational) studies
Assess safety of approved products in real world settings, under current standard of care
Patient Registries
Evaluate specified outcomes for a population defined by a particular disease, condition, or exposure
Post-Marketing Surveillance
Mandated by regulatory agencies to verify safety, tolerability and effectiveness of approved products
Pharmacovigilance Studies
Aimed at detecting, assessing and preventing prevention of short and long term Adverse effects or side effects of an approved product

RCTs, Open Label and Observational studies

Well defined, tightly controlled visit structure
Strict Inclusion / Exclusion criteria
Clinical research savvy PIs and site staff

Randomized, Open Label Studies
Open label studies involving randomization
Expanded Inclusion / Exclusion criteria Clinical research savvy PIs and site staff

Observational Studies
Broadly defined visit schedules that reflect real world settings
Reduced barriers for patients to enter studies
PIs and site staff are typically therapeutic focused medical practitioners

Focus on safety and efficacy in controlled study environments

Comparator and dosage compliance studies

Studies designed to collect data from real world settings, with none to minimal interventional procedures

Data collection and cleaning occurs in a controlled, experimental environment

Data collection and cleaning along the lines of RCTs

Data collection approach should reflect real world settings, and not force fit RCT expectations on Observational studies

The nature of data on observational studies should be a true representation of the area of research from where the data has been collected

StudiesDataData ManagementPatientsQuintiles