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7 - Prognostic tests and studies

Published online by Cambridge University Press:  04 August 2010

Thomas B. Newman  and
Michael A. Kohn
Thomas B. Newman
Affiliation:
University of California, San Francisco
Michael A. Kohn
Affiliation:
University of California, San Francisco
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Summary

Introduction

In previous chapters, we discussed issues affecting evaluation of diagnostic tests: how the reason to make a diagnosis may determine which tests should be done, how test reliability and accuracy are assessed, how to combine the results of tests with prior information to estimate the probability that a patient has a disease, and how to assess studies of diagnostic tests. In this chapter, we consider those same kinds of questions, with respect to prognostic tests.

Prognostic versus diagnostic tests

Prognosis is “a forecasting of the probable course and termination of an illness” (Webster's Unabridged Dictionary 2001). The main difference between prognostic tests and diagnostic tests is that, with prognostic tests, a time dimension is involved. With diagnostic tests, we are concerned with determining who does and does not have a disease. In this chapter, we begin with people who have a disease and try to predict their prognosis – that is, what will happen to them in the future. Thus, studies of prognostic tests generally have to be longitudinal in nature. That is, they need to follow a group of patients over time and allow measurement of incidence rather than just prevalence.

As was the case with studies of diagnostic tests, in which we compared test results among patients with and without the disease (a dichotomous variable), the outcome variable of a prognostic test study is generally also dichotomous – survival versus death, disease-free survival versus disease recurrence, and so on; each subject either does or does not develop that outcome.

Type
Chapter
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Evidence-Based Diagnosis , pp. 138 - 155
Publisher: Cambridge University Press
Print publication year: 2009

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References

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Hafler, D. A., Compston, A., et al. (2007). “Risk alleles for multiple sclerosis identified by a genomewide study.” N Engl J Med 357(9): 851–62.Google ScholarPubMed
Hilsenbeck, S. G., Clark, G. M., et al. (1992). “Why do so many prognostic factors fail to pan out?” Breast Cancer Res Treat 22(3): 197–206.CrossRefGoogle ScholarPubMed
Jellema, P., Windt, D. A., et al. (2007). “Prediction of an unfavourable course of low back pain in general practice: comparison of four instruments.” Br J Gen Pract 57(534): 15–22.Google ScholarPubMed
Kyzas, P. A., Loizou, K. T, et al. (2005). “Selective reporting biases in cancer prognostic factor studies.” J Natl Cancer Inst 97(14): 1043–55.CrossRefGoogle ScholarPubMed
Mackillop, W. J., and Quirt, C. F. (1997). “Measuring the accuracy of prognostic judgments in oncology.” J Clin Epidemiol 50(1): 21–9.CrossRefGoogle Scholar
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SUPPORT (1995). “A controlled trial to improve care for seriously ill hospitalized patients. The study to understand prognoses and preferences for outcomes and risks of treatments (SUPPORT). The SUPPORT Principal Investigators.” JAMA 274(20): 1591–8.CrossRef
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Webster's unabridged dictionary (2001). New York, Random House Reference.

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