Are Medical Doctors Scientists? Causal Inference Based on Observational Data
Keywords:Medical doctors, Clinician-scientist, Causal inference, Observational data
We present arguments for a view of what a clinician-scientist might be like, in the setting of everyday clinical practice. Clinical observations of good quality and completeness may, under suitable context or research framework, be viewed as evidence for claims of causation. Historical examples of clinicopathological observations in which causal claims were made and later confirmed, are briefly mentioned. We present in some detail a more recent causal inference framework in statistics, which is increasing accepted in practice, as well as a brief introduction to causal diagrams. Finally, we briefly present a view of a possible use of causal inference in the near future.
Miettinen O. Toward scientific medicine. New York: Springer, 2014.
Childers CP, Maggard-Gibbons M. Same data, opposite results? A call to improve surgical database. JAMA 2021;156:219-20.
Meyer MN, Heck PR, Holtzman GS, et al. Objecting to experiments that compare two unobjectionable policies or treatments. PNAS 2019; doi:10.1073/pnas.1820701116.
Singer C, Underwood EA. A short history of medicine. 2nd ed. Oxford: Clarendon Press, 1962.
Zampieri F, Zanatta A, Basso C, Thiene G. Caediovascular medicine in Morgagni’s De Sedibus: dawn of cardiovascular pathology. Cardiovasc pathol 2015;25:443-52.
R Shane T, Dominik TS, Martin MM, Mohammadali MS, et al. Giovanni Battista Morgagni (1682-1771): his anatomic majesty’s contributions to the neurosciences. Childs Nerv Syst 2012;28:1099-102.
Morgagni GB. De sedibus et causis morborum per anatomen indagatis libri quinque. Venice, 1761. English translation: Alexander B (transl). The seats and causes of diseases investigated by anatomy in five books. London: Miller & Cadell, and Johnson & Payne, 1769.
Rubin DB. Matched sampling for causal effects. Cambridge: Cambridge University Press, 2006.
Pearl J, Glymour M, Jewell NP. Causal inference in statistics: a primer. Chichester: John Wiley & Sons, 2016.
Pearl J, Mackenzie D. The book of why: the new science of cause and effect. London: Penguin Books, 2018.
Pearl J. Causality: models, reasoning, and inference. 2nd ed (corrected). Cambridge: Cambridge University Press, 2013.
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