Chapter adapted and updated, with permission, from Nicoll D et al. Guide to Diagnostic Tests, 7th ed. McGraw-Hill, 2017.
When used appropriately, diagnostic tests can be of great assistance to the clinician. Tests can be used for screening, ie, to identify risk factors for disease and to detect occult disease in asymptomatic persons. Identification of risk factors may allow early intervention to prevent disease occurrence, and early detection of occult disease may reduce disease morbidity and mortality through early treatment. Blood pressure measurement is recommended for preventive care of asymptomatic low-risk adults. Screening for breast, cervix, and colon cancer is also recommended, whereas screening for prostate cancer (using prostate-specific antigen [PSA]), lung cancer (in patients without a history of smoking), and thyroid cancer remains controversial. Screening without demonstrated benefits should be avoided. Optimal screening tests should meet the criteria listed in Table e2–1. Some screening test results (eg, rapid HIV antibody [Ab] tests) require confirmatory testing.
Table e2–1.Criteria for use of screening procedures. |Favorite Table|Download (.pdf) Table e2–1. Criteria for use of screening procedures.
|Characteristics of population |
| 1. Sufficiently high prevalence of disease. |
| 2. Likely to be compliant with subsequent tests and treatments. |
|Characteristics of disease |
| 1. Significant morbidity and mortality. |
| 2. Effective and acceptable treatment available. |
| 3. Presymptomatic period detectable. |
| 4. Improved outcome from early treatment. |
|Characteristics of test |
| 1. High sensitivity and specificity. |
| 2. Cost-effective and low risk. |
| 3. Confirmatory test available and practical. |
Tests can be used for diagnosis, ie, to help establish or exclude the presence of disease in symptomatic persons. Some tests assist in early diagnosis after onset of symptoms and signs; others assist in developing a differential diagnosis; others help determine the severity, activity, or stage of disease.
Tests can also be used in patient management. They can help (1) estimate prognosis and facilitate treatment decision making, (2) monitor the course of disease or treatment response (progression, stability, residual, or remission), (3) select drugs and adjust therapy, (4) detect disease recurrence, and (5) determine necessity of hospital admission and readiness for discharge.
One evolving field of medicine is personalized medicine, which involves tailoring treatment to the individual patient. Precision medicine is emerging as a tool to match patients with the appropriate treatment based on the precise biologic and molecular characteristics of an individual patient’s disease (cancer, in particular). As an example, only patients with breast cancer that shows overexpression of HER2 protein or extra copies of the HER2 gene or both could benefit from trastuzumab treatment. The associated companion diagnostics are rapidly evolving.
When ordering diagnostic tests, clinicians should weigh the potential benefits against the potential costs and adverse effects. Some tests carry a risk of morbidity or mortality—eg, cerebral angiogram leads to stroke in 0.5% of cases. The potential discomfort associated with tests such as colonoscopy may deter some patients from completing a diagnostic workup. The result of a diagnostic test may mandate additional testing or frequent follow-up, and the patient may incur significant cost, risk, and discomfort during follow-up procedures.
Furthermore, a false-positive test may lead to incorrect diagnosis, further unnecessary testing, or unnecessary treatment. Classifying a healthy patient as diseased based on a falsely positive diagnostic test can cause psychological distress and may lead to risks from unnecessary or inappropriate therapy. A screening test may identify disease that would not otherwise have been recognized and that would not have affected the patient. For example, early-stage prostate cancer detected by PSA screening in a 76-year-old man with known heart failure will probably not become symptomatic during his lifetime, and aggressive treatment may result in net harm. Similarly, routine preoperative testing should be discouraged, eg, preoperative testing needs to be considered carefully based on a targeted history, physical examination findings, and type of surgery.
The costs of diagnostic testing must also be understood and considered. Total costs may be high, patient out-of-pocket costs may be prohibitive, or cost-effectiveness may be unfavorable. Even relatively inexpensive tests may have poor cost-effectiveness if they produce very small health benefits. Factors adversely affecting cost-effectiveness include ordering a panel of tests when one test would suffice or option of reflex testing is available, ordering a test more frequently than necessary, ordering an inappropriate or incorrect test, ordering a duplicative test, and ordering a test for medical record documentation only. The value-based, operative question for test ordering is, “Will the test result help establish a diagnosis, affect a treatment decision, or help predict a prognosis?” If the answer is “no,” then the test is not justified. Unnecessary tests generate unnecessary labor, reagent, and equipment costs, and lead to high health care expenditures.
Molecular and genetic testing is readily available, and high-throughput DNA sequencing technology and cell-free DNA “liquid biopsy” for cancer testing are increasingly being applied in the clinical diagnostic realm. However, their cost-effectiveness and health outcome benefits need to be carefully examined. Determining when and how to incorporate genetic and molecular testing into practice in a cost-effective manner is often complicated but critical. Diagnostic genetic testing based on symptoms (eg, testing for fragile X in a boy with mental retardation) differs from predictive genetic testing (eg, evaluating a healthy person with a family history of Huntington disease) and from predisposition genetic testing, which may indicate relative susceptibility to certain hereditary conditions or response to certain drug treatment (eg, BRCA1/BRCA2 or HER2 testing for breast cancer). The outcome benefits of many new pharmacogenetic tests have not yet been established by prospective clinical studies; eg, there is insufficient evidence that genotypic testing for warfarin dosing leads to outcomes that are superior to those using conventional dosing algorithms, in terms of reduction of out-of-range international normalized ratios (INRs). Other testing (eg, testing for inherited causes of thrombophilia, such as factor V Leiden, prothrombin gene mutations, etc) has only limited value for managing patients, since knowing whether a patient has inherited thrombophilia generally does not change the intensity or duration of anticoagulation treatment. Hereditary disease testing, carrier testing (eg, for cystic fibrosis), and prenatal fetal testing (eg, for Down syndrome) often require counseling of patients so that there is adequate understanding of the clinical, social, ethical, and sometimes legal impact of the results.
Clinicians order and interpret large numbers of laboratory tests every day, and the complexity of these tests continues to increase. The large and growing test menu and the inconsistencies in nomenclature for many tests have introduced significant challenges for clinicians, ie, selecting the correct laboratory test and correctly interpreting the test results. Errors in test selection and test results interpretation are common and could impact patient safety but are often difficult to detect. Using evidence-based testing algorithms that provide guidance for test selection in specific disorders and expert-driven test interpretation (eg, reports and interpretative comments generated by clinical pathologists) can help decrease such errors. Consultation and collaboration with laboratory professionals (ie, pathologists, medical technologists) can also help improve the timeliness of diagnostic testing and optimize laboratory test utilization.
et al. The cost-effective laboratory: implementation of economic evaluation of laboratory testing. J Med Biochem. 2017 Jul;36(3):238–42.
et al. The evidence base for circulating tumour DNA blood-based biomarkers for the early detection of cancer: a systematic mapping review. BMC Cancer. 2017 Oct 23;17(1):697.
et al. Complexity of delivering precision medicine: opportunities and challenges. Am Soc Clin Oncol Educ Book. 2018 May 23;(38):998–1007.
et al. Evidence-based guidelines to eliminate repetitive laboratory testing. JAMA Intern Med. 2017 Dec 1;177(12):1833–9.
et al. Prostate-specific antigen-based screening for prostate cancer: evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2018 May 8;319(18):1914–31.
et al. Influence of educational, audit and feedback, system based, and incentive and penalty interventions to reduce laboratory test utilization: a systematic review. Clin Chem Lab Med. 2015 Feb;53(2):157–83.
et al. Cancer screening in the elderly: a review of breast, colorectal, lung, and prostate cancer screening. Cancer J. 2017 Jul/Aug;23(4):246–53.
et al. Screening for cervical cancer with high-risk human papillomavirus testing: updated evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2018 Aug 21;3207(7):687–705.
et al. Colorectal cancer screening: recommendations for physicians and patients from the U.S. Multi-Society Task Force on Colorectal Cancer. Am J Gastroenterol. 2017 Jul;112(7):1016–30.
et al. The evolving role of companion diagnostics for breast cancer in an era of next-generation omics. Am J Pathol. 2017 Oct;187(10):2185–98.
et al. Effectiveness of practices to support appropriate laboratory test utilization: a laboratory medicine best practices systematic review and meta-analysis. Am J Clin Pathol. 2018 Feb 17;149(3):197–221.
et al. Cancer screening in the United States, 2017: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2017 Mar;67(2):100–21.
et al. Review of clinical next-generation sequencing. Arch Pathol Lab Med. 2017 Nov;141(11):1544–57.