Key points are not available for this paper at this time.
Establishing flow cytometric DNA analysis as a clinical routine procedure requires adequate and proven guidelines, by which the data can be obtained and interpreted to directly influence management of the individual patient with a specific neoplasm. The present paper is intended as a contribution to such guidelines, of which only fragments are available today. We have previously described a system of methods, designed for routine flow cytometric DNA analysis. In the present status report our experience, based on approximately 18,000 samples (clinical and experimental) is summarised. Sample acquisition with fine-needle aspiration, storage at -80 degrees C, internal standardization by chicken (CRBC) and trout red blood cells (TRBC), staining with propidium iodide (PI), and analysis in the flow cytometer is recapitulated, with emphasis on previously unpublished aspects. The method of statistical analysis which has an integrating role is described in some detail. A lack of linearity between channel number and DNA content was determined experimentally, and the coefficient of variation (CV) was found to decrease with increasing channel number. The corrections in the algorithm of deconvolution made necessary by these findings are fundamental for estimating the end results. The zero point adjustment and procedures for changing from one batch of standards to another are described. A systematic approach to interpretation of DNA histograms is attempted and illustrated by data from clinical specimens of malignant lymphoma, breast cancer, small cell lung cancer, cancer of the oral cavity, and bladder cancer. Some problems are still unsolved and visual inspection is required to determine if the quality of the individual histogram is satisfactory. Inspection of the fluorescence/light scatter dot-plot provides additional information for the recognition of artifacts. The results stress that good quality DNA histograms with as small CVs as possible are important for interpretation of the data. It is essential that statistical methods are employed to extract the key end-point results. These are the number of subpopulations and their relative representation, and for each subpopulation the DNA index (DI) and the fractions of cells in the cell cycle phases. For the DNA data to have any rationally based impact on clinical decision making, it must be demonstrated that they have an independent prognostic value. Strategies for final evaluation are discussed. Multicenter trials on fresh material, to accrue quickly the number of patients necessary for firm conclusions, are suggested.
Vindeløv et al. (Mon,) studied this question.