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The Validation of Screening Tests: Meet the New Screen same as the Old Screen?

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Abstract

The focus of this report is to examine the process of validation of new screening tests designed to detect the problem gambler in research and practice settings. A hierarchical or phases of evaluation model is presented as a conceptual framework to describe the basic features of the validation process and its implications for application and interpretation of test results. The report describes a number of threats to validity in the form of sources of unintended bias that when unrecognized may lead to incorrect interpretations of study results and the drawing of incorrect conclusions about the usefulness of the new screening tests. Examples drawn from the gambling literature on problem gambling are used to illustrate some of the more important concepts including spectrum bias and clinical variation in test accuracy. The concept of zones of severity and the bias inherent in selecting criterion thresholds are reviewed. A definition of reference or study gold standard is provided. The use of 2-stage designs to establish validity by efficiently using reference standards to determine indices of accuracy and prevalence is recommended.

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Notes

  1. The term reference standard rather than gold standard is now preferred since gold standard connotes an errorless process whereas in practice this is rarely if ever true. Further, for most disorders there is no gold standard and alternative standards that are error-prone must be utilized. The study reference standard is an operational definition of diagnostic truth for evaluating the new test.

  2. The occurrence of errors in gold standards may be due to a number of sources, for example, the condition does not produce the expected biochemical changes, or an alternative condition mimics the biomarker changes of the condition of interest, a laboratory test may be mislabeled, a tumor is missed by MRI because it is too small, an image may be misinterpreted, a biopsy occurs outside of the affected tumor, the key is the term nearly infallible which reflects the rarity of errors (Reitsma et al. 2009). Some gold standards have error rates of nearly 5% or greater (Valenstein 1990).

  3. Any false positives among cases or false negatives among controls are ignored since it is assumed the test results apply on average and not to any individual (Schlesselman 1982).

  4. The use of a 2 × 2 table can lead to confusion since the role of prevalence (P) in calculating predictive values is not obvious. For example, from Table 1, PPV = TP/(TP + FP), however, TP = P × Se × N and FP = (1 − P) × (1 − Sp) × N, similar values apply to NPV.

  5. The version of DSM-IV used by Stinchfield (2003) is not identical to the NODS version used by Volberg (2002, 2003) and different rules for inclusion and exclusion were used. Further the results reported by Stinchfield were based on one-year intervals whereas those reported by Volberg were based on lifetime measures. These distinctions are real but would take us beyond the scope of this paper and are ignored for simplicity of presentation. The use of SOGS as reference standard for NODS was based on availability of data. The results in Table 4 are presented here solely for illustrative purposes.

  6. The measure of choice in Toce-Gerstein et al. (2009) was lifetime occurrences rather than one-year therefore the screen should not be interpreted in terms of screening for current problem gamblers.

  7. A familiar example would be evaluating a screening test to detect anxiety disorder and questions are included that might ask have you ever felt anxious when …

  8. Rectangular confidence intervals may be drawn for any point on the curve, there are other displays more commonly used (e.g., ellipses) for confidence intervals; the rectangular interval is much simpler to interpret.

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    Blase Gambino

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Appendices

Appendix 1

See Table 7.

Table 7 STARD check list for reporting diagnostic accuracy studies (Bossuyt et al. 2003)
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Appendix 2

See Table 8.

Table 8 The QUADAS tool (Whiting et al. 2003)
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Gambino, B. The Validation of Screening Tests: Meet the New Screen same as the Old Screen?. J Gambl Stud 28, 573–605 (2012). https://doi.org/10.1007/s10899-011-9285-6

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