Clinical prediction

Lodder J, Bamford J, Kappelle J, Boiten J. What causes false clinical prediction of small deep infarctions Stroke 1994 25 86-91. 

In fact, what we have been and are observing is the analytical phase in the quest for clinical predictions. As stated repeatedly in previous sections, this phase is indispensable because it alone can provide information on the parts of a system. For example, our understanding of interspecies differences in receptor and enzyme specificities had to await the advent of molecular... 

R2. Ramey, J. W., Seltman, H. J., and Toner, J. P., Superior analytic characteristics of an immuno-metric assay for gonadotropins also provides useful clinical prediction of in vitro fertilization outcomes. Fertil. Steril. 65, 661-663 (1996). 

A prognostic model is the mathematical combination of two or more patient or disease characteristics to predict outcome. Confusingly, prognostic models are also termed prognostic indexes, risk scores, probability models, risk stratification schemes or clinical prediction rules (Reilly and Evans 2006). To be useful, they must be shown to predict clinically relevant outcomes reliably. They must, therefore, be derived from a representative cohort in which outcome has been measured accurately. Next, they must be validated, not just in the data from which they were derived (internal validation) but also on data from independent cohorts (external validation) (Wyatt and Altman 1995 Justice et al. 1999 Altman and Royston 2000). Lastly, a model must be simple to use and have clinical credibility, otherwise it is unlikely to be taken up in routine clinical practice (Table 14.1). 

Reilly and Evans (2006) have defined five levels of evidence to assess the usefulness of a clinical prediction model (Box 14.4). 

Laupacis A, Sekar N, Stiell IG (1997). Clinical prediction rules. A review and suggested modifications of methodological standards. Journal of the American Medical Association 277 488-494... 

Kernan WN, Viscoli CM, Brass LM et al. (2000). The Stroke Prognosis Instrument II (SPIII) a clinical prediction instrument for patients with transient ischaemia and non-disabling ischaemic stroke. Stroke 31 456-462 Mathur KS, Kashyap SK, Kumar V (1963). Correlation of the extent and severity of atherosclerosis in the coronary and cerebral arteries. Circulation 27 929-934 Petty GW, Brown RD Jr., Whisnant JP et al. (2000). Ischemic stroke subtypes. 

Figure 1-5 Quadrant analysis of clinical predictivity. Reprinted from Regulatory Toxicology and Pharmacology, vol. 32/1, Olson et al., "Concordance of the Toxicity of Pharmaceuticals in Humans and in Animals 12, 2000, with permission from Elsevier.

Oliva PS, Hammill SC, Edwards WD. Cardiac rupture, a clinically predictable complication of acute myocardial infarc-... 

Development of novel antianginal therapy has suffered from the lack of predictive animal models. Some of the more interesting newer approaches include direct measurement of myocardial oxygen tension.electrocardiographic analysis in normal 5.>W> and diseased hearts,4-7 regional vascular resistance studies, blood flow distribution 9>50 and functional evaluation in normal hearts5l as well as in animals subjected to chronic coronary artery occlusion.52,53 The clinical predictability of these models remains undetermined. 

Surrogates are useful in the assessment of antimicrobial products, including antiseptics, provided they are standardized, reproducible, and have known predictive value. The methods proposed in the TFM, although standardized and reproducible, have not been validated to assess their clinical predictive value. In fact, none of the standardized surrogate methods used in antiseptic drug product development have been validated (TFM and ASTM reference). Thus, we are left to extrapolate from the premise that reduction of the microbial flora is a desired outcome, and if it is achieved, the product will be successful in the clinical setting. 

The model that is ultimately chosen should always be the simplest possible model which is still capable of providing an adequate description of the observed data. The kinetic properties of a model should always be understood if the model is used for clinical predictions. 

When an administered drug exhibits the characteristics of a two-compartment model, the difference between the distribution rate constant (a) and the slow (post-) distribution rate constant (/ ) plays a critical role. The greater the difference between these, the more conspicuous is the existence of a two-compartment model and, therefore, the greater is the need to apply all the equations for a two-compartment model. Failure to do so will, undoubtedly, result in inaccurate clinical predictions. If, however, the difference between the distribution and the slow post-distribution rate constant is small and will not cause any significant difference in the clinical predictions, regardless of the model chosen to describe the pharmacokinetics of a drug, then it may be prudent to follow the principle of... 

The cardinal clinical sign of fracture is bony tenderness and careful palpation of the injured ankle will often differentiate between a fracture and a soft tissue injury. Clinical prediction rules have been shown to be useful in determining which children with ankle injuries require X-ray investigation (Dayan et al. 2004 Myers et al. 2005). Adherence to such rules may miss the diagnosis of a small proportion of fractures but these will generally be those of little clinical significance. 

Cronin E (1972) Clinical prediction of patch test results. Trans St John s Hosp Derm Soc 58 153-162 Cronin E (ed) (1980) Metals, nickel. In Contact dermatitis. 

Clinical predictability of ICH S7B-related findings Predictable Questionable whether Predictable Predictable (for the moment)... 

Hess EP, Thiruganasambandamoorthy V, Wells GA, Erwin P, Jaffe AS, Hollander JE, Montori VM, Stiell IG. Diagnostic accuracy of clinical prediction rules to exclude acute coronary syndrome in the emergency department a systematic review. CJEM 2008 10 373-82. 

Hicks GE, Fritz JM, DeUtto A, McGill SM. Preliminary development of a clinical prediction rule for determining which patients with low back pain will respond to a stabilization exercise program. Arch Phys Med Rehabil. 2005 86 1753-62. 

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