Developing high‑performance prediction models for medical outcomes
Most of the current prediction models in health and medicine are inadequate. With some extra effort, high-performance prediction models can be developed.
About Abhaya Indrayan
Prof Indrayan is the only biostatistician in India as of 2025 to be honored with the fellowship of the Indian Academy of Sciences (of Dr CV Raman fame). He completed MS and PhD from the Ohio State University in a record time of three years. He established the first Department of Biostatistics and Medical Informatics in India – that too in a non-PG medical institution – in the year 1995, which was later emulated by SGPGI (Lko) and JIPMER (Py). He retired as Head of this department in 2010 and is currently (2025) working as a Biostatistics Consultant at Max Healthcare.
Prof Indrayan is respected as the top biostatistician in the country with more than 300 publications, including a large number of his own research on medical biostatistics. He has authored 6 books, three of which are published in the US for international audience, and more than 20 chapters. He has completed nearly 40 projects for the World Health Organization, the World Bank, and the UNAIDS. He has also been running an online course for an international audience for the past 20 years in collaboration with a US institute. Prof Indrayan has been a Visiting Faculty at the Ohio State University and a Visiting Research Scientist at the University of Massachusetts. He has presented his work in 17 international conferences.
Prof Indrayan is serving biostatistics in several ways. He has developed a medically integrated curriculum of biostatistics for medical under- and postgraduate students that medicalizes the subject of biostatistics. His publications on Personalized Statistical Medicine, medical uncertainties, and the conundrum of P-values are widely acclaimed. Among his original ideas are the smoking index, objective measurement of an individual’s positive health, scoring for assessing the quality of the process of medical research from choosing a problem to its publication, a simple and robust method of measurement of agreement without Bland-Altman limits, correct method for assessing predictive performance of a model, and ‘promote heart disease, stop cancer’ by research on choosing the cause of death in old age.
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The emphasis of my work is on
Developing statistical medicine (as a branch of medicine - whereas medical statistics is a branch of statistics) by promoting the use of statistical tools such as models, scoring systems, and indexes in clinical medicine for individual care, as a help to clinicians, just as laboratory medicine is today.