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Causal Inference in Law: An Epidemiological Perspective

Published online by Cambridge University Press:  20 January 2017

Bob Siegerink
Affiliation:
Center for Stroke Research, Charité, Univeristitätsmedizin Berlin, Berlin, Germany and Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Nehterlands
Wouter den Hollander
Affiliation:
Institute for Private Law, Leiden University, Leiden, the Netherlands
Maurice Zeegers
Affiliation:
Maastricht University, School of Nutrition, Toxicology and Metabolism & Maastricht Forensic Institute, Maastricht, the Netherlands
Rutger Middelburg
Affiliation:
Center for Clinical Transfusion Research, Sanquin Research, Leiden, the Netherlands, and Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands

Extract

Causal inference lies at the heart of many legal questions. Yet in the context of complicated disease litigation, in particular, the causal inquiry is beset with difficulties due to gaps in scientific knowledge concerning the precise biological processes underlying such diseases. Civil courts across the globe, faced with increased litigation on such matters, struggle to adhere to their judicial fact-finding and decision-making role in the face of such scientific uncertainty. An important difficulty in drawing evidentially sound causal inferences is the binary format of the traditional legal test for factual causation, being the ‘but for’ test, which is based on the condicio-sine-qua-non principle. To the question ‘would the damage have occurred in the absence of the defendant's wrongful behaviour’ the ‘but for’ test requires a simple yes or no answer. This is increasingly deemed unsatisfactory in cases in which, given the state of science, true causation cannot possibly be determined with certainty.

Type
Articles
Copyright
Copyright © Cambridge University Press 2016

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References

1 See for instance Deakin, S., Johnston, A., Markesinis, B. Markesinis and Deakin's Tort Law (7 th ed.), Oxford: Clarendon Press 2013, pp. 218256 Google Scholar.

2 Joung, H. Rha, & Saver, L.J., ‘The Impact of Recanalization on Ischaemic Stroke Outcome: a Meta-Analysis’, Stroke 38 (2007), pp. 967–73Google Scholar.

3 Lansberg, M.G. et al., ‘Antithrombotic and Thrombolytic Therapy for Ischaemic Stroke: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines’, Chest 141 (2012), e601S–36SGoogle Scholar.

4 Goya Wannamethee, S. et al., ‘Smoking Cessation and the Risk of Stroke in Middle-Aged Men’, JAMA 274 (1995), pp. 155–60CrossRefGoogle Scholar.

5 Milionis, H.J. et al., ‘Statin Therapy after First Stroke Reduces 10- year Stroke Recurrence and Improves Survival’, Neurology 72 (2009), pp. 1816-22CrossRefGoogle ScholarPubMed.

6 For more background reading on the theory of causation, please refer to: Pearl, J., Causality: Models, Reasoning, and Inference, Cambridge University Press, 2000; 2nd edition, 2009.

7 Rothman, K.J. et al., ‘Causation and Causal Inference in Epidemiology’, Am. J. Public Health 95 (2005) Suppl. 1, pp. S144-50CrossRefGoogle ScholarPubMed.

8 Rothman, K.J., Greenland, S., Lash, T.L., Modern Epidemiology (third revised edition), Lippincott Williams & Wilkins 2008 Google Scholar.

9 Rothman, K.J., ‘Causes’, Am. J. Epidemiol 104 (1976), pp, 587-92CrossRefGoogle ScholarPubMed.

10 Zuurbier, S.M. et al., ‘Decompressive Hemicraniectomy in Severe Cerebral Venous Thrombosis: a Prospective Case Series’, Journal of. Neurology 259 (2012), pp. 1099-105CrossRefGoogle ScholarPubMed.

11 Rothman, K.J., Greenland, S., Lash, T.L., Modern Epidemiology (third revised edition), Lippincott Williams & Wilkins 2008 Google Scholar.

12 Senn, S., Crossover-trials in clinical research, Wiley 1993 Google Scholar.

13 Maclure, M. et al, ‘Should we use a case-crossover design?’, Annual Review of Public Health (2000), pp. 193221 CrossRefGoogle ScholarPubMed.

14 Vlak, M.H.M. et al., ‘Trigger Factors and Their Attributable Risk for Rupture of Intracranial Aneurysms: a Case-crossover Study’, Stroke 42 (2011), pp. 1878–82CrossRefGoogle ScholarPubMed.

15 Rothman, K.J., Greenland, S., Lash, T.L., Modern Epidemiology (third revised edition), Lippincott Williams & Wilkins 2008 Google Scholar.

16 For more background information on the statistical approaches that can be applied to investigate causal relationships, please refer to Berzuini, C., Dawid, S., Bernadinell, L., (editors), ‘Causality: Statistical Perspectives and Applications’, (Wiley, 2012)CrossRefGoogle Scholar

17 See for example the website of the Centre for evidence based medicine with the title ‘Levels of evidence’, <http://www.cebm.net/index.aspx?o=1025> (21 July 2014).

18 Vandenbroucke, J.P., ‘When are observational studies as credible as randomised trials?’, Lancet 363 (2004), pp. 1728–31CrossRefGoogle ScholarPubMed.

19 Haack, S., Manifesto of a Passionate Moderate, Chicago: University of Chicago Press 1998 Google Scholar.

20 Vandenbroucke, J.P., ‘Alternative Medicine: A “Mirror Image” for Scientific Reasoning in Conventional Medicine’, Annals of Internal Medicine 135 (2001), pp. 507511 CrossRefGoogle ScholarPubMed.

21 Hill refers to these nine points as ‘aspects of …(an) association’ that should be considered before deciding on the interpretation of causation. These points are: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment and analogy. See also Hill, A.B., ‘The Environment and Disease: Association or Causation?’, Proceedings of the Royal Society of Medicine (1965), pp. 295300 Google ScholarPubMed.

22 Morabia, A., ‘On the Origin of Hill's Causal Criteria’, Epidemiology 2 (1991), pp. 367369 CrossRefGoogle ScholarPubMed.

23 Phillips, C.V. et al., ‘The Missed Lessons of Sir Austin Bradford Hill’, Epidemiology Perspectives and Innovations 1 (2004), p. 3 CrossRefGoogle ScholarPubMed.

24 Hoge Raad 31 March 2006, ECLI:NL:HR:2006:AU6092, reachable through <http://uitspraken.rechtspraak.nl/#ljn/AU6092> (in Dutch; 9 December 2014).

25 Hoge Raad 31 maart 2006, ECLI:NL:HR:2006:AU6092. See also, more recently, Hoge Raad 14 december 2012, ECLI:NL:HR:2012:BX8349. On these cases, see Castermans, A.G. & Hollander, P.W. den, ‘Omgaan met onzekerheid. Proportionele aansprakelijkheid, artikel 6:101 BW en de leer van de kansschade’, NTBR 2013, pp. 185195 (in Dutch)Google Scholar.

26 The situation under which the attributable fraction can be interpreted as the aetiological fraction are described in Kenneth J. Rothman, Sander Greenland, Timothy L. Lash. Modern Epidemiology, third revised edition, (Lippincott Williams & Wilkins, 2008)

27 Greenland, S., ‘Relation of Probability of Causation to Relative Risk and Doubling Dose: a Methodologic Error That Has Become a Social Problem’, American Journal of Public Health 89 (1999), pp. 1166–9CrossRefGoogle ScholarPubMed.