Development and validation of clinical risk prediction models for rare outcomes

Date:

Tue, 25 Apr 2023

Time:

11am – 12pm [Singapore [GMT +8]

Location:

Conference Room 1, Level 10
Tahir Foundation Building (MD1)
National University of Singapore
12 Science Drive 2, Singapore 117549

Details:

You are cordially invited to the ON-SITE SSHSPH Staff Research Round.
We look forward to your attendance and we hope for an interesting discussion.

Refreshments will be provided at 10.30am, do drop by to hang out for a bit before the session starts.
We will also be having a Lucky Draw at the end of the session, register yourself and stand a chance to win a special prize!
*Only Attendees will be included in the Lucky draw*

Abstract:

Risk prediction models are frequently developed in clinical research to predict patients’ future health outcome such as death or state of illness due to disease and/or to classify patients into clinical risk groups (low, medium and high). Predictions from these models are useful to make joint decision with both patient and clinician for future course of treatment. However, clinicians will be reluctant to use these models unless they can trust on predictions. To maximize the prediction accuracy and clinical utility of these models, it is essential to confirm that the models are rigorously developed and validated and evaluated. However, the standard process of model development and validation faces serious problems when the outcome is rare. This talk discusses the methodological challenges and possible solutions of model development and validation for data with rare outcomes. Issues are discussed providing example of predictive models for binary and survival data separately and illustrating them using both simulated and practical data.

Speakers:

Dr M. Shafiqur Rahman
Professor of Applied Statistics, Insititute of Statistical Research and Training, University of Dhaka

M. Shafiqur Rahman is currently working as a Professor of Applied Statistics at the Institute of Statistical Research and Training, University of Dhaka. He completed BSc Honours and MSc in Statistics from University of Dhaka, Bangladesh. He then completed 2nd MSc in Statistics from University of Nottingham, and PhD in Medical Statistics from Unversity College London, UK. His main research areas include casual inference, development and validating risk prediction models, and mixed effect models, focusing on development of new statistical methods for analysing data in public health and medical research. In addition to teaching and research, he is involved with statistical consultancy services for various national and international organizations. Moreover, he is involved as PI and Co-PI of many research projects and as an associate editor and reviewer of many peer reviewed journals such as PLOS ONE, BMC Medical Research Methodology, Statistics in Medicine, International Journal of Cardiology. He is a member of the Bangladesh Statistical Association, International Biometric Society, International Statistical Institute, International Society of Clinical Biostatistics and an educational ambassador of the American Statistical Association from Bangladesh.