The fog of war.
This was a metaphor coined by the Prussian military analyst Carl von Clausewitz in his book, On War (1832), to describe the confusion, and uncertainty that results from the chaos of warfare.
Comparable to the fog of war is the fog of treatment since it may take weeks or sometimes even months before the efficacy of a particular therapy or therapeutic regimen is known or understood with any clarity. Significant time is lost in the case of non-response. In general, the sooner an effective therapy is started the better the outcome. Conversely, the longer it takes to start an effective therapy, the worse the outcome since most diseases progress or get worse over time, which makes them harder to treat. Therefore, patients would benefit tremendously if the therapeutic efficacy were known or predicted sooner rather than later so those with a non-response or a low likelihood of one could start another more effective treatment.
To counter and cut through the fog of treatment requires accurate, real-time information preferentially from validated biological markers or biomarkers. These are measured biological indicators that can be used to predict prognoses, identify responders and nonresponders, and monitor therapeutic outcomes. Proteins, nucleic acids, enzymes, antigens, antibodies, cells, lipids, and imaging scans may serve as biomarkers.
Examples of clinically validated FDA approved biomarkers include HbA1c (glycosylated hemoglobin A1c) during antidiabetic therapy, the prothrombin time (PT) or international normalized ratio (INR) during anticoagulant therapy, prostate-specific antigen (PSA) in prostate cancer, dHIV RNA (viral load) and CD4 T lymphocyte cell (CD4) count during antiretroviral therapy (ART), B-type natriuretic peptides, as well as N-terminal pro-BNP, in heart failure, Her2/neu receptor expression for trastuzumab (Herceptin) therapy, C-reactive protein (CRP) in rheumatoid arthritis, and EGFR, ALK and MET mutational status since these are direct targets of approved inhibitory anticancer agents.
As legendary baseball player, Yogi Berra, said, “It is difficult to make predictions, especially about the future.” However, aided by the rise of big data science, computational biology, and artificial intelligence (AI), we imagine a not-too-distant future where a surge of validated next gen disease — and therapy-specific biomarkers, the next frontier in development, will become available to be used like an early warning radar system that can immediately see through even the densest fog of treatment.