What is “Normal?”
The biologic LEDs referred to above are indicators of cellular function or dysfunction. These biomarkers usually are obtained from the patient’s blood or urine and are ascribed a range or span which is considered “normal.” Unless we know what the patient’s baseline is and track test results over time, we have no idea if the status of the patient’s tissue or organ is stable, improving or worsening. In other words, the essence of biomarker analysis involves the tracking of a laboratory test(s) over time. When this is done for purposes of appraising the status of a tissue, organ or body system, then we increase our ability to optimize health outcomes.
Returning to our analogy with the automobile, we check the oil level with a dipstick or gauge. Using the results of our baseline measurement, we know if the level is dropping lower. We also obtain a sense of how rapidly the level may be dropping if assessments are being made at periodic intervals. Both inputs—the absolute level and the rate of change—affect our response to this situation. This use of chronology incorporates the important considerations of baseline value plus subsequent testing over the dimension of time. This is critical in the appraisal of dynamic biologic systems involving all life forms. A few examples are appropriate at this time.
A Clinical Vignette
A former employee of mine tearfully asked me to help evaluate her mother’s condition. Her mother (LT) had just been diagnosed with stomach cancer. At the time of her diagnosis, she was already jaundiced due to extensive metastases to the liver. LT was also anemic because the primary stomach cancer had eroded the gastric wall causing bleeding into the gastrointestinal tract. I obtained all of the patient’s medical records, which included those from years before her diagnosis so that I could get a true sense of the pace of what now appeared to be fulminant disease. In assessing LT’s anemia, the results of past CBC (complete blood count) tests were reviewed. The CBC includes the white cell count, hemoglobin, hematocrit and the platelet count. It also includes other measurements such as the mean cell hemoglobin concentration (MCHC) of the red blood cell as well as the size of the red blood cell (mean cell volume or MCV). I found a baseline hematocrit of 45% obtained three years before the diagnosis. Sorting all the medical records chronologically, I could track the fall of the hematocrit to the low 40s, and from there into the 37% to 39% range, and then eventually to her severely anemic value of 31% (Figure 2).
|The change in a biologic input over time provides a superior perspective about any alteration in biologic function. The hematocrit is a highly stable biomarker and a fall in value from a stable baseline of 45% to 42% would justify repeating the study. The drop to 37% should have prompted a major clinical investigation to determine the cause of anemia. |
In addition, the mean cell volume (MCV) had progressively dropped over time from 88 to 85, to 78 and then to 74 at the time of diagnosis. Values of less than 80 should be an alert to iron deficiency anemia. A trend indicating falling values, even though still within the range of “normal,” should be a red alert to an astute M.D. Causes of iron deficiency anemia to be considered would include blood loss due to ulcer disease in the stomach or duodenum, malignancy anywhere in the gastrointestinal tract, hiatal hernia with or without esophagitis, helicobacter pylori gastritis, celiac sprue and atrophic gastritis.[5,6] In LT’s case, regardless of the cause of her abnormal blood picture, her illness had declared itself through changing laboratory findings years before any clinical symptoms. The M.D. (medical detective) had not discerned this. Instead of an early diagnosis for LT, she was diagnosed with far-advanced stomach cancer with extensive liver metastases. Her condition was so weakened by her advanced presentation that anti-cancer therapy was compromised. She died within a few months of her diagnosis.
If a proper assessment of LT’s lab results had been done as part of her medical assessment, her diagnosis of stomach cancer would have been made years earlier, perhaps when the cancer was still localized to the stomach and before it had a chance to metastasize to the liver. A similar assessment of the liver status also revealed that the level of alkaline phosphatase had been slowly and steadily climbing—even within the so-called “normal” range. Unfortunately, no note was made of this until the result rose beyond the upper limit of normal and then entered into “abnormal” territory. When the patient was finally diagnosed, her liver was so extensively involved with cancer that she was already jaundiced. Physicians and patients must both realize that biologic indicators don’t go from normal to abnormal as though a light switch were turned from “off” to “on.” These biomarkers declare themselves more in the manner of a dimmer switch that raises the level of light progressively. More often than not, changes in biomarker levels are apparent on retrospective review for years before the pathologic condition has become blatant. Thus, the change over time or trend is a critical concept in biologic systems that mandates attention.
Evaluating Laboratory Dynamics Adds to Baseline and Trend Strategies
A second and fortunately less dramatic case history involved a 54-year-old patient (RK) with a diagnosis of prostate cancer made in June 2003. He had a family history of prostate cancer (PC) involving his father and one of his three brothers. He was therefore stratified as a high-risk patient due to family history that indicated he had hereditary prostate cancer (HPC).[7-9]
Because of this, RK had diligently obtained PSA (Prostate Specific Antigen) values every year starting at the age of 40. His baseline PSA was 0.6 ng/ml. Over the course of the next 10 years, the PSA had slowly climbed to 1.0. At age 51, the PSA was 1.4 and shortly after RK’s 52nd birthday it had risen to 2.0. His family physician assured RK that this was still well within the “normal” range for PSA (1.0-4.0 ng/ml). A year later the PSA was 2.5 and at age 54 it had risen to 4.4. This prompted RK to seek a further opinion with a urologist who ordered a free PSA percentage, which came back as 6.8%. This result was highly worrisome for the presence of prostate cancer. Using the data inputs of RK’s age, total PSA and free PSA values, his probability of having PC was 87%. A transrectal ultrasound of the prostate with 12 biopsy cores was performed and confirmed a diagnosis of PC with a Gleason score of (4,4) involving 6 of the 12 cores. (A Gleason score is a method for classifying the cellular differentiation of cancerous tissues. High numbers indicate the presence of cancer.) He was advised to have a radical prostatectomy (RP), which was performed in July 2003. The specimens obtained at the time of RP revealed PC with involvement of two pelvic lymph nodes.
RK and his family were upset. Why was the diagnosis of PC not made earlier?
A more scientific analysis of RK’s biologic LEDs might have led to an earlier diagnosis. In the case of prostate cancer, the PSA values are the markers to watch. Inspecting the PSA values with a focus on the actual rate of increase of the PSA over time suggested that his biologic system was in disarray and needed more attention. In other words, besides looking at an absolute value of a PSA determination, or even viewing the changes in values over time, more objective and more comprehensive evidence is obtainable. Such determinations reflect laboratory dynamics. In this case, it involves a derivative of PSA testing called PSA velocity or PSAV. This provides more cogent information on the status of the patient’s prostate gland. The PSAV relates information about the increase in PSA in the blood over time (acceleration) using the measurement of nanograms (ng) per milliliter(ml) per year(yr). The medical literature has established that a PSAV of 0.75 ng/ml/yr or higher is an indicator of high risk for the presence of PC.[11-15] Therefore, RK’s biologic LEDs suggested the presence of a “malfunction,” but this was missed because the focus of the M.D. was on an absolute value, and not laboratory dynamics such as the acceleration of the PSA, i.e., the PSAV.
Using Combined Variable Analysis Further Enhances Medical Detective Work
When it comes to understanding biologic systems in the context of laboratory evaluation or other diagnostics, the importance of substantiating data inputs, i.e., additional variables of information, must be stressed. Finding multiple variables of information suggesting a malfunction adds further circumstantial evidence that increases the accuracy of diagnosis. This is incorporated in the concept of combined variable analysis and it applies to all analytic data. In the context of PSA dynamics, additional variables of information might also include:
- PSA doubling time (PSADT)
- Free PSA percentage and its derivatives:
- Free PSA percentage velocity
- Free PSA slope
- Free PSA doubling time and related inputs
- PSA density (ratio of PSA to the prostate gland volume)
- Free PSA density
When we review a patient’s biologic LEDs in this manner, we elevate our analysis and enhance our ability to provide the patient with an early warning system. In the case of RK, this was done retrospectively. The PSA doubling times are shown in Table 1. The average PSA doubling time for prostate cancer at the time of diagnosis is approximately 24 months. Conditions such as benign prostate hyperplasia (BPH) usually have PSADT’s of more than 12 years (144 months). Healthy prostate tissue, in contrast, has a PSA doubling time as long as 54 ± 13 years. RK had a PSADT of about two years as far back as May of 2000, three years before his diagnosis was established.
|In the case of RK, despite so-called normal PSA values of less than 4.0 ng/ml, his PSAV, PSADT, and free PSA percentages all were consistent with a diagnosis of prostate cancer. The halving times relating to the free PSA percentages, though not a test currently in use, have relevance to the diagnosis and prognosis of prostate cancer. |
The free PSA percentage test reflects that PSA comprises two major subunits of PSA: the free PSA and the complexed PSA. The complexed PSA is associated with prostate cancer; the free PSA is not. The higher the free PSA%, the less likely that the patient has prostate cancer. The lower the free PSA%, the more likely that there is more complexed PSA and the presence of PC. The serum from RK’s past lab tests had been frozen and stored in the laboratory. These specimens were obtained and free PSA percentages were determined. Table 1 shows that in May 1997 free PSA was 48%; in May 1999 it was 40%; and in May 2000 it was determined to be 25%, and with each passing year it dropped lower and lower.
The concept of using the derivatives of a specific test to understand dynamics of biologic testing can be applied to any biologic LED. And because biologic events represent living, metabolizing and sometimes growing biologic entities, it is entirely reasonable that such dynamics are of major importance.
Others have taken this approach when it comes to using the free PSA percentage to determine PSA density. In the case of RK, instead of PSA doubling times, free PSA percentage halving times were calculated from 1997 to 2003. Although such calculations and their interpretations have yet to be published in the medical literature, it was clear that an inexorable fall in free PSA percentage started after 1997. This was expressed in the approximate halving times of 91, 18, 25, 20 and 15 months relating to the respective time periods of 1997-1999, 1999-2000, 2000-2001, 2001-2002 and 2002-2003. In other words, the malignant condition was expressing itself with shorter and shorter halving times of the free PSA percentage. This was a biologic expression of a growing malignancy consisting of prostate cancer cells making more and more complexed PSA and therefore dropping the free PSA percentage lower.