DNA ploidy and cell-cycle analysis: tools for assessment of cancer prognosis

DNA ploidy and cell cycle analysis as measured by flow cytometry (FC) and image analysis (IA) have moved out of the realm of the research laboratory to become valid clinical tests used in the assessment of prognosis of the cancer patient. Although much information on the relationship of DNA ploidy/%S-phase analysis to patient prognosis is available in the literature, the data are not presented in such a way as to be helpful in clinical decision making. Because predictive values and confidence intervals, which measure the likelihood that a given clinical test will rule in or rule out a clinical outcome, were not calculated in previous reviews, conclusions about the clinical utility of these analyses were not possible. Using the available raw data on DNA ploidy and %S-phase analysis from previously published papers, predictive values and confidence limits were calculated for specific clinical presentations. In several such clinical situations (tumor type, stage, etc.), predictive value of greater than 90% was derived. We conclude that in these situations DNA ploidy and %S-phase analysis can be used to predict clinical outcome, to design treatment, and to guide patient management. The evaluation of the clinical utility of these tests must ultimately rest on prospective trials which show that randomized arms respond to treatment regimens dependent upon the DNA ploidy and %S-phase status.