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Optimal treatment levels in cancer therapy

1972; Wiley; Volume: 30; Issue: 1 Linguagem: Inglês

10.1002/1097-0142(197207)30

1097-0142

Dan H. Moore, Mortimer L. Mendelsohn,

Computational Drug Discovery Methods

CancerVolume 30, Issue 1 p. 97-106 ArticleFree Access Optimal treatment levels in cancer therapy Dan H. Moore II PhD, Corresponding Author Dan H. Moore II PhD Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa.Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St., Philadelphia, Pa. 19104===Search for more papers by this authorMortimer L. Mendelsohn MD, PhD, Mortimer L. Mendelsohn MD, PhD Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa.Search for more papers by this author Dan H. Moore II PhD, Corresponding Author Dan H. Moore II PhD Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa.Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St., Philadelphia, Pa. 19104===Search for more papers by this authorMortimer L. Mendelsohn MD, PhD, Mortimer L. Mendelsohn MD, PhD Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa.Search for more papers by this author First published: July 1972 https://doi.org/10.1002/1097-0142(197207)30:1 3.0.CO;2-MCitations: 24AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract A two-part method is proposed for optimizing treatment levels in cancer therapy. The first part makes use of a treatment characteristic (TC) curve as a graphical method for summarizing the responses of normal and tumor tissue to therapy. For treatment responses that are cumulative normal, the TC curve, formed by plotting the probit probability of ablation against the probit probability of complication, is a straight line whose slope is the ratio of standard deviations of the two responses and whose position measures the relative sensitivity of the cancer and normal tissue. TC lines are completely defined by studying a homogeneous group of patients at two treatment levels within the same protocol. In the second part of the method, all possible outcomes of therapy are assigned costs or weights. This assignment converts the probit TC line into an expected loss function which estimates the effectiveness of therapy. The minimum of this function locates the optimum probabilities of ablation and complication and is the best therapy, given the therapist's cost structure, the protocol, and the class of patients being studied. References 1 Finney, D. J.: Probit Analysis, 2nd ed. Cambridge, England, Cambridge University Press, 1952. 2 Hammond, K. R.: Computer graphics as an aid to learning. Science 172: 903– 908, 1971. 3 Lusted, L. B.: Introduction to Medical Decision Making. Springfield. Charles C Thomas, 1968; pp. 98– 140. 4 Mendelsohn, M. L.: Radiotherapy and tolerance. In Frontiers of Radiation Therapy and Oncology, vol. 5. Basel New York, Karger, 1971 (in press). 5 Swets, J. A., Tanner, W. P., Jr., and Birdsall, T. G.: Decision processes in perception. In Signal Detection and Recognition by Human Observers. New York, John Wiley & Sons, 1964; pp. 3– 57. Citing Literature Volume30, Issue1July 1972Pages 97-106 ReferencesRelatedInformation