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7 Qualifying Biomarkers
Pages 65-73

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From page 65...
... Dr. Vonderscher discussed what is involved in transforming observational or exploratory biomarkers into valid biomarkers that can be used in making regulatory decisions. The ideal biomarker Vonderscher outlined the characteristics of an ideal biomarker for kidney toxicity: • It should be visible early, prior to histopathological changes, and should be indicative after active damage.
From page 66...
... Given this extensive list of characteristics, a panel of biomarkers rather than any single ideal biomarker will likely be needed to characterize nephrotoxicity. Qualification of Nephrotoxicity biomarkers Before attempting to establish pathways for clinical qualification of biomarkers, Novartis qualified a set of nephrotoxicity biomarkers in animals.
From page 67...
... The marker urinary clusterin exhibited properties similar to those of Kim-1, but it had more false negatives -- that is, animals with levels below the threshold but with histopathology grades of 1 or 2. To obtain a quantitative measure of how well the various biomarkers predicted lesions, the team performed an ROC (receiver operating characteristic)
From page 68...
... The data shown represent the fold change in serum creatinine at increasing dose levels. Results indicate that serum creatinine was not a particularly useful biomarker because, although some of the middle-dose animals had histopathology grades 1 and 2, they were comparable to control animals and only the animals in the high-dose group had serum creatinine above the control threshold.
From page 69...
... Unlike creatinine, Kim-1 may be a useful biomarker for cisplatin-induced tubular necrosis/ apoptosis. Kim-1 was elevated not only in the high-dose group but also in the middle-dose group (in animals that showed histopathology grades of 1 or 2)
From page 70...
... To generate an ROC curve, the true positive rate was graphed against the false positive rate as the threshold was varied continuously. The area under the ROC curve gives a quantitative measure of how good the predictions are: in the case of a perfect predictor, with a threshold that has all the positives above and all the negatives below, the area under the curve will be 1.0; in the case of a random predictor, the area under the curve will be 0.5.
From page 71...
... Part of the reason that the ROC 1 Area Under Curve: 0.9 Random = 0.5 0.8 Creatinine = 0.83 0.7 BUN = 0.81 0.6 Kim -1 = 0.95 Sensitivity 0.5 Clusterin = 0.93 0.4 0.3 0.2 78 Diseased 0.1 291 Controls 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1-Specificity FIGURE 7-4  ROC (receiver operating characteristic) analysis to compare biomarkers for tubular necrosis mostly proximal (but sometimes not clearly localized)
From page 72...
... score for Kim-1 dropped to 0.95 when all the different compounds and lesions were included was the inclusion of one compound that caused lesions in the tubular collecting ducts, where Kim-1 is not expressed and so cannot serve as an effective marker. In a similar analysis for glomerular alteration and damage (see Figure 7-5)
From page 73...
... A panel will be necessary in particular to specify different localizations in the kidney and to differentiate among toxicity types. While Novartis and the PSTC have not yet achieved this capability, their ultimate goal is to assemble a collection of kidney toxicity markers that will be visible prior to histopathological changes and can serve as a panel covering most nephrotoxicity.


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