In clinical trials, it’s not always possible to measure hard endpoints like cardiovascular disease events and cancer remission rates. Studies that use clinical outcomes often dichotomize these variables, and as a result, they need to have a large number of participants and be long in duration to detect differences between groups.
Again, this type of research is expensive and not always feasible. In many scenarios, a more practical alternative is to focus on intermediate markers. Intermediate markers are biomarkers associated with a clinical outcome.1
For example, C-reactive protein (CRP) is a molecule that is strongly associated with inflammation, and you can often find that CRP levels increase when inflammation increases.2–4 Because inflammation is associated with coronary heart disease (CHD)5–8, an investigator may choose to focus on decreasing levels of inflammation in a clinical trial (measured by CRP), rather than focus on how many CHD-related deaths the intervention prevents.
If the changes in an intermediate marker can robustly predict changes in a hard endpoint, and if it’s part of the primary pathway of the clinical outcome, then your biomarker can be considered a surrogate marker for that clinical outcome.1 (I’m not sure if CRP is a good surrogate outcome for CHD events, just used it as an example).
Low-density lipoprotein (LDL) is considered an excellent surrogate marker for CHD because reducing LDL levels also seems to reduce the number of CHD events.9,10 Unfortunately, this can all go wrong if the intermediate marker is associated with a clinical outcome, but is not involved in the causal pathway of the outcome and is confounded by other phenomena.
A great example of this is the story of high-density lipoprotein (HDL) and myocardial infarction (heart attacks). Several studies had found associations between low levels of HDL, often considered “good cholesterol,” and heart attacks.11–17
So, it shouldn’t come as a surprise that a drug (torcetrapib) was produced by Pfizer that attempted to increase the amount of HDL with the hopes that it would reduce the number of CVD events.
A group of researchers administered the drug to thousands of patients.18 The drug was successful in changing the lipids of the participants to more favorable numbers. Patients who received the drug had a 24.9% decrease in LDL and a 72.1% increase in HDL. Seems pretty great. However, the number of deaths increased by 58% and the number of heart attacks increased by 21%.
A systematic review and meta-analysis19 published in the BMJ a few years later concluded the following after pooling studies that focused on interventions that primarily increased HDL and interventions that primarily decreased LDL,
“Available data suggest that simply increasing the amount of circulating high-density lipoprotein cholesterol does not reduce the risk of coronary heart disease events, coronary heart disease deaths, or total deaths. The results support reduction in low-density lipoprotein cholesterol as the primary goal for lipid modifying interventions.”
Svensson20 provides us with a very lovely table showing other scenarios for which a drug had a favorable effect on a surrogate marker but had a negative impact on the clinical outcome.
What does this tell us? That focusing only on improving surrogate markers is not a very good idea if there is not much concordance between trials that focus on surrogates and trials that focus on hard endpoints. Until we’ve established a robust causal link between a surrogate marker and a hard endpoint, we shouldn’t be seduced by surrogates.
1. Hulley SB. Designing Clinical Research. Lippincott Williams & Wilkins; 2007.
2. Bray C, Bell LN, Liang H, et al. Erythrocyte Sedimentation Rate and C-reactive Protein Measurements and Their Relevance in Clinical Medicine. WMJ: official publication of the State Medical Society of Wisconsin. 2016;115(6):317-321.
3. Chew KS. What’s new in Emergencies Trauma and Shock? C-reactive protein as a potential clinical biomarker for influenza infection: More questions than answers. Journal of Emergencies, Trauma, and Shock. 5(2):115. doi:10.4103/0974-2700.96477
4. Pepys MB, Hirschfield GM. C-reactive protein: A critical update. The Journal of Clinical Investigation. 2003;111(12):1805-1812. doi:10.1172/JCI18921
5. Frangogiannis NG. Regulation of the inflammatory response in cardiac repair. Circ Res. 2012;110(1):159-173. doi:10.1161/CIRCRESAHA.111.243162
6. Hansson GK. Inflammation, atherosclerosis, and coronary artery disease. N Engl J Med. 2005;352(16):1685-1695. doi:10.1056/NEJMra043430
7. Libby P. Inflammation and cardiovascular disease mechanisms. Am J Clin Nutr. 2006;83(2):456S-460S. doi:10.1093/ajcn/83.2.456S
8. Ruparelia N, Chai JT, Fisher EA, Choudhury RP. Inflammatory processes in cardiovascular disease: A route to targeted therapies. Nat Rev Cardiol. 2017;14(3):133-144. doi:10.1038/nrcardio.2016.185
9. Cholesterol Treatment Trialists’ (CTT) Collaboration, Fulcher J, O’Connell R, et al. Efficacy and safety of LDL-lowering therapy among men and women: Meta-analysis of individual data from 174,000 participants in 27 randomised trials. Lancet. 2015;385(9976):1397-1405. doi:10.1016/S0140-6736(14)61368-4
10. Taylor F, Huffman MD, Macedo AF, et al. Statins for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2013;(1):CD004816. doi:10.1002/14651858.CD004816.pub5
11. Assmann G, Schulte H, von Eckardstein A, Huang Y. High-density lipoprotein cholesterol as a predictor of coronary heart disease risk. The PROCAM experience and pathophysiological implications for reverse cholesterol transport. Atherosclerosis. 1996;124 Suppl:S11-20.
12. Curb JD, Abbott RD, Rodriguez BL, et al. A prospective study of HDL-C and cholesteryl ester transfer protein gene mutations and the risk of coronary heart disease in the elderly. J Lipid Res. 2004;45(5):948-953. doi:10.1194/jlr.M300520-JLR200
13. Gordon T, Castelli WP, Hjortland MC, Kannel WB, Dawber TR. High density lipoprotein as a protective factor against coronary heart disease. The Framingham Study. Am J Med. 1977;62(5):707-714.
14. Gordon DJ, Probstfield JL, Garrison RJ, et al. High-density lipoprotein cholesterol and cardiovascular disease. Four prospective American studies. Circulation. 1989;79(1):8-15.
15. Rahilly-Tierney CR, Spiro 3rd A, Vokonas P, Gaziano JM. Relation between high-density lipoprotein cholesterol and survival to age 85 years in men (from the VA normative aging study). Am J Cardiol. 2011;107(8):1173-1177. doi:10.1016/j.amjcard.2010.12.015
16. Sharrett AR, Ballantyne CM, Coady SA, et al. Coronary heart disease prediction from lipoprotein cholesterol levels, triglycerides, lipoprotein(a), apolipoproteins A-I and B, and HDL density subfractions: The Atherosclerosis Risk in Communities (ARIC) Study. Circulation. 2001;104(10):1108-1113.
17. Turner RC, Millns H, Neil HA, et al. Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS: 23). BMJ. 1998;316(7134):823-828.
18. Barter PJ, Caulfield M, Eriksson M, et al. Effects of torcetrapib in patients at high risk for coronary events. N Engl J Med. 2007;357(21):2109-2122. doi:10.1056/NEJMoa0706628
19. Briel M, Ferreira-Gonzalez I, You JJ, et al. Association between change in high density lipoprotein cholesterol and cardiovascular disease morbidity and mortality: Systematic review and meta-regression analysis. BMJ. 2009;338:b92. doi:10.1136/bmj.b92
20. Svensson S, Menkes DB, Lexchin J. Surrogate outcomes in clinical trials: A cautionary tale. JAMA Intern Med. 2013;173(8):611-612. doi:10.1001/jamainternmed.2013.3037