BlueCross and BlueShield of Montana Medical Policy/Codes
Biomarker Assays for Assessing Risk of Type 2 Diabetes
Chapter: Medicine: Tests
Current Effective Date: July 18, 2013
Original Effective Date: July 18, 2013
Publish Date: July 18, 2013

The following description of prediabetes and diabetes risk is taken from the National Diabetes Information Clearinghouse, through the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Prediabetes is a condition in which blood glucose levels are higher than normal but not high enough for a diagnosis of diabetes. This condition is sometimes called impaired fasting glucose (IFG) or impaired glucose tolerance (IGT), depending on the test used to diagnose it. People with prediabetes are at increased risk of developing type 2 diabetes, formerly called adult-onset diabetes or noninsulin-dependent diabetes. Type 2 diabetes is sometimes defined as the form of diabetes that develops when the body does not respond properly to insulin, as opposed to type 1 diabetes, in which the pancreas makes little or no insulin.

Studies have shown that most people with prediabetes develop type 2 diabetes within 10 years, unless they lose 5 to 7 percent of their body weight—about 10 to 15 pounds for someone who weighs 200 pounds—by making changes in their diet and level of physical activity. (1,2)

Risk Factors for Prediabetes and Type 2 Diabetes

The American Diabetes Association recommends that testing to detect prediabetes and type 2 diabetes be considered in adults without symptoms who are overweight or obese and have one or more additional risk factors for diabetes. In those without these risk factors, testing should begin at age 45.

Risk factors for prediabetes and diabetes-in addition to being overweight or obese or being age 45 or older-include the following (1,2):

  • being physically inactive;
  • having a parent or sibling with diabetes;
  • having a family background that is African American, Alaska Native, American Indian, Asian American, Hispanic/Latino, or Pacific Islander;
  • giving birth to a baby weighing more than 9 pounds or being diagnosed with gestational diabetes;
  • having high blood pressure (140/90 or above) or being treated for high blood pressure;
  • having an HDL, or "good," cholesterol level below 35 mg/dL or a triglyceride level above 250 mg/Dl;
  • having polycystic ovary syndrome;
  • having impaired fasting glucose (IFG) or impaired glucose tolerance (IGT) on previous testing;
  • having other conditions associated with insulin resistance, such as severe obesity or acanthosis nigricans;
  • having a history of cardiovascular disease.

Insulin Resistance and Prediabetes Can Be Reversed

Physical activity and weight loss help the body respond better to insulin. By losing weight and being more physically active, people with insulin resistance or prediabetes may avoid developing type 2 diabetes.

The Diabetes Prevention Program (DPP) and other large studies have shown that people with prediabetes can often prevent or delay diabetes if they lose a modest amount of weight by cutting fat and calorie intake and increasing physical activity-for example, walking 30 minutes a day 5 days a week. Losing just 5 to 7 percent of body weight prevents or delays diabetes by nearly 60 percent. In the DPP, people aged 60 or older who made lifestyle changes lowered their chances of developing diabetes by 70 percent. Many participants in the lifestyle intervention group returned to normal blood glucose levels and lowered their risk for developing heart disease and other problems associated with diabetes. The DPP also showed that the diabetes drug metformin reduced the risk of developing diabetes by 31 percent.

People with insulin resistance or prediabetes can help their body use insulin normally by being physically active, making wise food choices, and reaching and maintaining a healthy weight. Physical activity helps muscle cells use blood glucose for energy by making the cells more sensitive to insulin. (1,2)

PreDx Diabetes Risk Score

The PreDx Diabetes Risk Score® (DRS) (Tethis Bioscience) is a simple fasting blood test that determines absolute risk of developing type 2 diabetes within 5 years. PreDx DRS measures multiple serum biomarkers associated with biological pathways implicated in the development and progression of type 2 diabetes, and utilizes a complex algorithm based on the quantification of these markers to produce a personalized risk score on a scale of 1 (lower risk) to 10 (highest risk) that correlates with an individual’s absolute risk of developing diabetes within 5 years. The targeted patient group includes those patients who meet the above risk criteria, with the additional criteria of family history of diabetes. The PreDx DRS is a biochemical assay of 7 analytes: glucose, HbA1C, insulin, hs-CRP, adoponectin, ferritin, and interleukin 2-receptor alpha). (7)


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Blue Cross and Blue Shield of Montana (BCBSMT) considers Biomarker assays for assessing risk of Type 2 Diabetes experimental, investigational and unproven (e.g., PreDx Diabetes Risk Score™).


In a June 2009 study, McKenna et al. hypothesized that a risk prediction tool relying primarily on measurements from glucose and HbA1C lack specificity, and incorporating markers from multiple biological pathways that underlie disease pathogenesis would combine the advantages of robust risk prediction with the clinical convenience of a routine blood test. Their objective was to validate the DRS, a simple fasting blood test assessing multiple biomarkers that predict 5-year risk of type 2 diabetes, on an independent population. The test was performed on the Botnia cohort, a Finnish family-based study designed to identify genetic factors associated with development of type 2 diabetes. The participants had 5-year outcomes available for the study. The authors concluded that the DRS stratified the Botnia cohort according to 5-year risk of type 2 diabetes accurately; the DRS reclassified at-risk patients into categories of low, moderate and high risk; DRS effectively redistributed patients among presumed high-risk groups; and DRS may be useful in developing effective diabetes prevention programs for patients identified as highly vulnerable to diabetes. (3)

In July 2009, Kolberg et al. conducted a study to develop a model for assessing the 5-year risk of developing diabetes from a panel of 64 circulating candidate biomarkers. Subjects were selected from the Inter99 cohort, a longitudinal population-based study of about 6,600 Danes in a nested case-control design with the primary outcome of 5-year conversion to type 2 diabetes. Nondiabetic subjects, aged 39 years, with BMI ≥25 kg/m2 at baseline were selected. Baseline fasting serum samples from 160 individuals who developed type 2 diabetes and from 472 who did not were tested. An ultrasensitive immunoassay was used to measure of 58 candidate biomarkers in multiple diabetes-associated pathways, along with six routine clinical variables. Statistical learning methods and permutation testing were used to select the most informative biomarkers. Risk model performance was estimated using a validated bootstrap bias-correction procedure. A model using six biomarkers (adiponectin, C-reactive protein, ferritin, interleukin-2 receptor A, glucose, and insulin) was developed for assessing an individual’s 5-year risk of developing type 2 diabetes. This model has a bootstrap-estimated area under the curve of 0.76, which is greater than that for A1C, fasting plasma glucose, fasting serum insulin, BMI, sex-adjusted waist circumference, a model using fasting glucose and insulin, and a noninvasive clinical model. The authors concluded that a model incorporating six circulating biomarkers provides an objective and quantitative estimate of the 5-year risk of developing type 2 diabetes, performs better than single risk indicators and a noninvasive clinical model, and provides better stratification than fasting plasma glucose alone. (4)

Also in July 2009, Urdea et al. conducted a validation of a multimarker model for assessing risk of type 2 diabetes from the 5-year prospective study of 6,784 Danish people (Inter99).  They described the training and validation of the PreDx™ Diabetes Risk Score (DRS) model in a clinical laboratory setting using baseline serum samples from subjects in the Inter99 cohort, a population-based primary prevention study of cardiovascular disease. Among 6784 subjects free of diabetes at baseline, 215 subjects progressed to diabetes (converters) during five years of follow-up. A nested case-control study was performed using serum samples from 202 converters and 597 randomly selected nonconverters. Samples were randomly assigned to equally sized training and validation sets. Seven biomarkers were measured using assays developed for use in a clinical reference laboratory. The PreDx DRS model performed better on the training set (area under the curve [AUC] = 0.837) than fasting plasma glucose alone (AUC = 0.779). When applied to the sequestered validation set, the PreDx DRS showed the same performance (AUC = 0.838), thus validating the model. This model had a better AUC than any other single measure from a fasting sample. Moreover, the model provided further risk stratification among high-risk subpopulations with impaired fasting glucose or metabolic syndrome. (5)

In a paper presented at the 6th World Congress on Prevention of Diabetes and its Complications, April 8–11, 2010, in Dresden, Germany, Kolberg et al. discussed performance of a multi-marker diabetes risk score on the insulin resistance atherosclerosis study (IRAS), a multi-ethnic U.S. cohort. Their study concluded that 1) the performance of the DRS does not differ across the different ethnic subpopulations in the IRAS study population, an important consideration when the test is being applied in routine clinical practice; 2) DRS is better than other risk assessment tools, including fasting plasma glucose, fasting insulin, BMI, and HOMA-IR; and 3) DRS provides additional value over the current clinical practice of using fasting glucose levels to identify individuals at elevated risk for incident diabetes. The DRS test can easily be implemented in clinical practice and identifies individuals who are genuinely at high risk for developing type 2 diabetes and for whom diabetes prevention strategies should be emphasized. (6)

The above 4 studies were sponsored by, or otherwise connected to Tethys Bioscience. The studies were case series, and no randomized controlled trials have been done that show improved outcomes by knowing this risk score for patients who exhibit standard risk factors for developing type 2 diabetes. Therefore, at this time PreDx DRS is considered experimental, investigational and unproven.


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Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy. They may not be all-inclusive.

The presence or absence of procedure, service, supply, device or diagnosis codes in a Medical Policy document has no relevance for determination of benefit coverage for members or reimbursement for providers. Only the written coverage position in a medical policy should be used for such determinations.

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ICD-9 Codes

Experimental, investigational and unproven for all diagnoses.

ICD-10 Codes

Experimental, investigational and unproven for all diagnoses.

Procedural Codes: 81506
  1. Insulin Resistance and Prediabetes. U.S. Department of Health and Human Services National Institutes of Health. National Institute of Diabetes and Digestive and Kidney Diseases. NIH Publication No 09-4893. October, 2008.
  2. Am I at Risk for Type 2 Diabetes? Taking Steps to Lower Your Risk of Getting Diabetes. National Diabetes Information Clearinghouse (NDIC), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH). July 23, 2012. Available at (accessed November 2, 2012).
  3. McKenna M, Lyssenko V, et al. Validation of the Diabetes Risk Score, a Multi-Marker Panel that Assesses the Risk of Type 2 Diabetes: Combined Results of the Inter99 and Botnia Studies. Presented at 68th Scientific Sessions of the American Diabetes Association (ADA), June 5–9, 2009, New Orleans, Louisiana.
  4. Kolberg K,  Jørgensen T, et al. Development of a Type 2 Diabetes Risk Model From a Panel of Serum Biomarkers From the Inter99 Cohort. Diabetes Care July 2009; 32:1207-1212.
  5. Urdea M, Kolberg J, et al. Validation of a Multimarker Model for Assessing Risk of Type 2 Diabetes from a Five-Year Prospective Study of 6784 Danish People (Inter99). J Diab Sci and Tech July, 2009; 3(4): 748-755.
  6. Kolberg J, Wagenknecht L, et al. Performance of a multi-marker diabetes risk score on the Insulin Resistance Atherosclerosis Study (IRAS), a multi-ethnic US cohort. Presented at the 6th World Congress on Prevention of Diabetes and its Complications, April 8–11, 2010, Dresden, Germany.
May 2013  New 2013 BCBSMT medical policy.  Biomarker assays for assessing risk of Type 2 Diabetes is considered experimental, investigational and unproven (e.g., PreDx Diabetes Risk Score™).   
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Biomarker Assays for Assessing Risk of Type 2 Diabetes