Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster display session: Breast cancer - early stage, locally advanced & metastatic, CNS tumours, Developmental therapeutics, Genitourinary tumours - prostate & non-prostate, Palliative care, Psycho-oncology, Public health policy, Sarcoma, Supportive care

4439 - Deployment of advanced real-world data (RWD) analytics for the accelerated recruitment of patients into an ongoing metastatic castrate-resistant prostate cancer (mCRPC) trial, together with the development of a sophisticated patient referral network

Date

22 Oct 2018

Session

Poster display session: Breast cancer - early stage, locally advanced & metastatic, CNS tumours, Developmental therapeutics, Genitourinary tumours - prostate & non-prostate, Palliative care, Psycho-oncology, Public health policy, Sarcoma, Supportive care

Topics

Bioethical Principles and GCP

Tumour Site

Prostate Cancer

Presenters

Michael Cushion

Citation

Annals of Oncology (2018) 29 (suppl_8): viii271-viii302. 10.1093/annonc/mdy284

Authors

M.G. Cushion

Author affiliations

  • Analytics Centre Of Excellence, IQVIA, NI 9JY - London/GB
More

Resources

Abstract 4439

Background

Proprietary advanced analytics were applied within US RWD, e.g. medical/prescription claims and physician reference data, to identify high potential sites and physicians treating eligible mCRPC patients, with the aim of accelerating recruitment into an ongoing mCRPC clinical trial. Furthermore, a bespoke methodology to identify physician-to-investigator relationships was used to implement an advanced data driven patient referral network.

Methods

Relevant standard diagnosis, drug, and procedure codes were applied to medical and prescription claims datasets and cross-linked with physician reference data, to identify medical oncologists treating the target patient population. Physicians were also referenced to their affiliated sites. Shared patient counts between investigators and local physicians were also quantified, providing valuable insights into physician-to-investigator relationships to prioritise and leverage into a patient referral network.

Results

Selected results summarised below: ∼20k eligible patients were identified - 270 sites each with ≥20 eligible patients were identified ∼2k oncologists treating eligible patients and with trial experience in the past year were identified ∼4k shared patients between targeted physicians and trial investigators were identified.

Conclusions

To facilitate faster patient access to effective medicines, novel methods such as those outlined above are required to optimise clinical trial operations and increase efficiency. Together with the innovative use of RWD to find eligible mCRPC patients and the physicians and sites treating these, we implemented sophisticated techniques to quantify shared patient counts between identified physicians and investigators. This created a foundation for a referral network that has been successfully implemented, as an alternative to the lengthy and costly initiation of a new site(s). This approach would be invaluable in future trials with ever smaller patient populations, for example within rare diseases and precision medicine.

Clinical trial identification

Legal entity responsible for the study

IQVIA.

Funding

IQVIA.

Editorial Acknowledgement

Disclosure

The author has declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.