Prognostic vs Predictive Biomarkers: What is the Difference?
Tue Dec 22 2020
Prognostic vs Predictive Biomarkers: What is the Difference?
Biomarkers can be broadly divided into two main types: prognostic and predictive. Biomarkers can be either, or in some cases they could be both: prognostic and predictive. The difference between a biomarker’s prognostic and predictive value can be highly useful in charting a treatment plan for patients and determining treatment outcomes. This article will discuss the difference between the two types of biomarkers and detail the significance of suPAR as a prognostic, as well as, predictive biomarker. Read about what suPAR is here.
suPAR as a Prognostic and Predictive Biomarker
suPAR is a biomarker with both prognostic and predictive values. Studies supporting the prognostic and predictive value of suPAR are as follows:
- A 2012 study published in BMC Medicine supported the prognostic value of suPAR for sepsis. The study also reported that suPAR has clearly established predictive value that could be used for triaging patients in the Intensive Care Unit (ICU)5.
- According to a 2015 study, suPAR is a prognostic biomarker that could be used for risk stratification in the emergency department6.
- According to a 2019 study published in Journal of Clinical Oncology, circulating suPAR represents a novel prognostic marker in pancreatic adenocarcinoma patients undergoing tumor resection7.
- As per a 2015 study published in the International Journal of Cancer, circulating suPAR levels would be higher in patients who do not respond to cetuximab treatment for colorectal cancer than in patients who respond. This finding supports the predictive value of suPAR in oncology8.
Prognostic Biomarkers: Definition and Examples
A prognostic biomarker is defined as a clinical or biological characteristic that provides information on the most probable patient health outcome irrespective of the treatment1. Therefore, any biomarker that can inform about the likely outcome of disease (disease recurrence or progression or death) independent of the treatment received can be classified as a prognostic biomarker. It is also important to note that a prognostic biomarker may reveal the likely outcome of a disease even in the absence of any treatment2.
Common Prognostic Biomarkers3:
- Breast cancer genes- BRCA 1 and 2- are prognostic biomarkers that can help determine the likelihood of recurrence of breast cancer.
- Prostate-specific antigen (PSA) is used as a prognostic biomarker for assessing disease progression in prostate cancer patients.
- Plasma fibrinogen can be used as a prognostic biomarker for patients with chronic obstructive pulmonary disorder (COPD) to determine risk for exacerbation.
- C-reactive protein (CRP) is a prognostic biomarker that can be used for patients with a history of myocardial infarction or unstable angina to identify risk of recurrent coronary artery disease.
Predictive Biomarkers: Definition and Examples
A predictive biomarker is defined as a clinical or biological characteristic that indicates the degree of benefit a patient can have from a treatment, compared to their condition at baseline1. A predictive biomarker can help determine which treatment could be the best option for a patient, depending on their overall health status and extent of disease2. A predictive biomarker can also help identify patients who are more likely than other patients with the same disease to have a favourable outcome to a treatment plan or pharmaceutical drug or medical procedure4.
Common Predictive Biomarkers4:
- Cystic fibrosis transmembrane conductance regulator (CFTR) mutations is a predictive biomarker that can identify patients who respond more favourably than others to particular treatments.
- Human leukocyte antigen allele (HLA)–B*5701 genotype can be used to evaluate human immunodeficiency virus (HIV) patients before onset of abacavir treatment in order to identify patients at risk for severe skin reactions.
- In women with platinum-sensitive breast cancer, breast cancer genes- BRCA 1 and 2 mutations can be used as a predictive biomarker to identify patients who are likely to respond to ADP-ribose-PARP inhibitors.
