{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T21:41:08Z","timestamp":1790890868438,"version":"4.1.0"},"reference-count":13,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2006,3,29]],"date-time":"2006-03-29T00:00:00Z","timestamp":1143590400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancer"],"published-print":{"date-parts":[[2006,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>BACKGROUND<\/jats:title><jats:p>Patients with newly diagnosed cancer may request an estimate of their prospects for long\u2010term survival. Unfortunately, standard estimates of survival may be outdated, because they do not reflect recent advances. The authors present a projection method that incorporates trends in survival and provides more up\u2010to\u2010date estimates of long\u2010term survival for newly diagnosed patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>METHODS<\/jats:title><jats:p>The projection method fits a regression model to interval relative survival and includes a parameter associated with a trend on diagnosis year. The cumulative relative survival rate (CRS) in a target year is calculated by multiplying the projected interval survival rates for that year. To investigate the predictive ability of the projection approach and to develop model\u2010selection rules, data from the Surveillance, Epidemiology, and End Results Program and the Connecticut tumor registry were used to recreate data that were available at a particular time in the past, and those data were used to project survival for specified target years.<\/jats:p><\/jats:sec><jats:sec><jats:title>RESULTS<\/jats:title><jats:p>The projection method was better at predicting the survival of recently diagnosed patients than current methods, especially long\u2010term survival for patients who had disease sites with an increasing and stable trend in survival. The authors predicted that the 15\u2010year CRS for patients who were diagnosed in 2003 will be 61% for all cancer sites combined, 57% for colorectal cancer, 82% for female breast cancer, 53% for ovarian cancer, and 97% for prostate cancer.<\/jats:p><\/jats:sec><jats:sec><jats:title>CONCLUSIONS<\/jats:title><jats:p>Although the projection method was more speculative than other methods that are aligned more closely with current observed data, it offered the possibility of providing improved estimates of long\u2010term survival for recently diagnosed patients. Caution should be used when applying these methods for cancer sites where there has been a dramatic uptake of screening, e.g., prostate cancer, for which the projected results may be overly optimistic. Cancer 2006. Published 2006 by the American Cancer Society.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cncr.21803","type":"journal-article","created":{"date-parts":[[2006,3,29]],"date-time":"2006-03-29T16:47:58Z","timestamp":1143650878000},"page":"2039-2050","source":"Crossref","is-referenced-by-count":19,"title":["Estimates of long\u2010term survival for newly diagnosed cancer patients"],"prefix":"10.1002","volume":"106","author":[{"given":"Angela B.","family":"Mariotto","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret N.","family":"Wesley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathleen A.","family":"Cronin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karen A.","family":"Johnson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric J.","family":"Feuer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2006,3,29]]},"reference":[{"key":"e_1_2_5_2_2","unstructured":"Surveillance Epidemiology and End Results (SEER) Program. SEER Stat Database: incidence SEER 9 Registries public\u2010use. Nov 2002 Sub (1973\u20132000)\u2014National Cancer Institute released April 2003 based on the November 2002 submission. Available at URL:http:\/\/www.seer.cancer.gov[accessed March2005]."},{"key":"e_1_2_5_3_2","volume-title":"SEER cancer statistics review, 1975\u20102000","author":"Ries LAG","year":"2003"},{"key":"e_1_2_5_4_2","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwf071"},{"key":"e_1_2_5_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(02)11199-8"},{"key":"e_1_2_5_6_2","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/31.2.456"},{"key":"e_1_2_5_7_2","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2002.99.060"},{"key":"e_1_2_5_8_2","first-page":"101","article-title":"The relative survival rate: a statistical methodology","volume":"6","author":"Ederer F","year":"1961","journal-title":"Natl Cancer Inst Monogr."},{"key":"e_1_2_5_9_2","volume-title":"Survival analysis techniques for censored and truncated data","author":"Klein JP","year":"1997"},{"key":"e_1_2_5_10_2","volume-title":"Differences between Brenner et al. and NCI Methods for calculating period survival. Technical report 2003\u201002","author":"Cronin K","year":"2003"},{"key":"e_1_2_5_11_2","doi-asserted-by":"publisher","DOI":"10.2307\/2347789"},{"key":"e_1_2_5_12_2","doi-asserted-by":"publisher","DOI":"10.1097\/00001648-200003000-00014"},{"key":"e_1_2_5_13_2","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2002.20.5.1192"},{"key":"e_1_2_5_14_2","volume-title":"Manual for staging of cancer","author":"American Joint Committee on Cancer","year":"1988"}],"container-title":["Cancer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fcncr.21803","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/acsjournals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cncr.21803","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T11:27:20Z","timestamp":1760268440000},"score":1,"resource":{"primary":{"URL":"https:\/\/acsjournals.onlinelibrary.wiley.com\/doi\/10.1002\/cncr.21803"}},"subtitle":["A projection approach"],"short-title":[],"issued":{"date-parts":[[2006,3,29]]},"references-count":13,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2006,5]]}},"alternative-id":["10.1002\/cncr.21803"],"URL":"https:\/\/doi.org\/10.1002\/cncr.21803","archive":["Portico"],"relation":{},"ISSN":["0008-543X","1097-0142"],"issn-type":[{"value":"0008-543X","type":"print"},{"value":"1097-0142","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006,3,29]]}}}