Speaker
Description
In pharmaceutical research and preclinical development data below the lower limit of quantitation are quite common although sometimes not properly dealt with. Beyond time-to-event settings measured data above a general or even subject specific upper limit of quantitation are less common.
Malignant tumor cells can metastasize. When tumor cells metastasize they might cause new tumors called secondary or metastatic tumors. Effective metastasis treatment should at best prevent generating secondary tumors or at least limit their numbers. Specific animal-tumor models are used where the number of metastases in lungs is quite easily to be determined after the sacrifice of the animals. For physiological reasons this holds true up to a certain number of metastases, above that number metastases become connected and therefore indistinguishable – resulting in values above a limit of quantitation as right censored count values.
As the main focus of research projects is usually a comparison of the efficacy of a treatment vs. a vehicle control or between different treatments to decide with which compound at which dose to proceed, both a proper test strategy and effect estimation is inevitable. Based on such a real-life example, modeling strategies will be discussed along with some thoughts on how to communicate the results.
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