Dynamic prognostication using conditional survival estimates. Issue 20 (1st August 2013)

• Record Type: Journal Article
• Authors: Zabor, Emily C.; Gonen, Mithat; Chapman, Paul B.; Panageas, Katherine S.
• Is Part Of: Cancer. Volume 119:Issue 20(2013)
• Page Start: 3589
• Page End: 3592
• Publication Date: 2013-08-01
• Subjects: conditional survival -- prognosis -- patient counseling -- survivorship -- melanoma; Cancer -- Periodicals; Cancer -- Cytopathology -- Periodicals; 616.99405
• DOI: 10.1002/cncr.28273
• Languages: English
• ISSNs: 0008-543X

Abstract

Abstract : Measures of prognosis are typically estimated from the time of diagnosis. However, these estimates become less relevant as the time from diagnosis increases for a patient. Conditional survival measures the probability that a cancer patient will survive some additional number of years, given that the patient has already survived for a certain number of years. In the current study, the authors analyzed data regarding patients with stage III melanoma to demonstrate that survival estimates from the time of diagnosis underestimate long‐term survival as the patient is followed over time. The probability of surviving to year 5 for patients at the time of presentation compared with patients who had already survived for 4 years increased from 72% to 95%, 48% to 90%, and 29% to 86%, respectively, for patients with substage IIIA, IIIB, and IIIC disease. Considering the major role played by survival estimates during follow‐up in patient counseling and the development of survivorship programs, the authors strongly recommend the routine use of conditional survival estimates. Cancer 2013;119:3589–3592 . © 2013 American Cancer Society . Abstract : Conditional survival estimates provide dynamic prognostication using the information that a given patient has survived some time after baseline, and are obtained through the baseline Kaplan‐Meier estimates. The routine use of conditional survival estimates is strongly recommended by the authors.