Literature DB >> 25417239

Providing clinicians and patients with actual prognosis: cancer in the context of competing causes of death.

Nadia Howlader1, Angela B Mariotto2, Steven Woloshin2, Lisa M Schwartz2.   

Abstract

BACKGROUND: To isolate progress against cancer from changes in competing causes of death, population cancer registries have traditionally reported cancer prognosis (net measures). But clinicians and cancer patients generally want to understand actual prognosis (crude measures): the chance of surviving, dying from the specific cancer and from competing causes of death in a given time period.
OBJECTIVE: To compare cancer and actual prognosis in the United States for four leading cancers-lung, breast, prostate, and colon-by age, comorbidity, and cancer stage and to provide templates to help patients, clinicians, and researchers understand actual prognosis.
METHOD: Using population-based registry data from the Surveillance, Epidemiology, and End Results (SEER) Program, we calculated cancer prognosis (relative survival) and actual prognosis (five-year overall survival and the "crude" probability of dying from cancer and competing causes) for three important prognostic determinants (age, comorbidity [Charlson-score from 2012 SEER-Medicare linkage dataset] and cancer stage at diagnosis). RESULT: For younger, healthier, and earlier stage cancer patients, cancer and actual prognosis estimates were quite similar. For older and sicker patients, these prognosis estimates differed substantially. For example, the five-year overall survival for an 85-year-old patient with colorectal cancer is 54% (cancer prognosis) versus 22% (actual prognosis)-the difference reflecting the patient's substantial chance of dying from competing causes. The corresponding five-year chances of dying from the patient's cancer are 46% versus 37%. Although age and comorbidity lowered actual prognosis, stage at diagnosis was the most powerful factor: The five-year chance of colon cancer death was 10% for localized stage and 83% for distant stage.
CONCLUSION: Both cancer and actual prognosis measures are important. Cancer registries should routinely report both cancer and actual prognosis to help clinicians and researchers understand the difference between these measures and what question they can and cannot answer. We encourage them to use formats like the ones presented in this paper to communicate them clearly. Published by Oxford University Press 2014.

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Year:  2014        PMID: 25417239      PMCID: PMC4841170          DOI: 10.1093/jncimonographs/lgu022

Source DB:  PubMed          Journal:  J Natl Cancer Inst Monogr        ISSN: 1052-6773


  21 in total

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2.  Assessing non-cancer-related health status of US cancer patients: other-cause survival and comorbidity prevalence.

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3.  Impact of comorbidity on survival among men with localized prostate cancer.

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4.  Improved estimates of cancer-specific survival rates from population-based data.

Authors:  Nadia Howlader; Lynn A G Ries; Angela B Mariotto; Marsha E Reichman; Jennifer Ruhl; Kathleen A Cronin
Journal:  J Natl Cancer Inst       Date:  2010-10-11       Impact factor: 13.506

5.  Effect of age, tumor risk, and comorbidity on competing risks for survival in a U.S. population-based cohort of men with prostate cancer.

Authors:  Timothy J Daskivich; Kang-Hsien Fan; Tatsuki Koyama; Peter C Albertsen; Michael Goodman; Ann S Hamilton; Richard M Hoffman; Janet L Stanford; Antoinette M Stroup; Mark S Litwin; David F Penson
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6.  Rethinking screening for breast cancer and prostate cancer.

Authors:  Laura Esserman; Yiwey Shieh; Ian Thompson
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7.  Cancer survival in five continents: a worldwide population-based study (CONCORD).

Authors:  Michel P Coleman; Manuela Quaresma; Franco Berrino; Jean-Michel Lutz; Roberta De Angelis; Riccardo Capocaccia; Paolo Baili; Bernard Rachet; Gemma Gatta; Timo Hakulinen; Andrea Micheli; Milena Sant; Hannah K Weir; J Mark Elwood; Hideaki Tsukuma; Sergio Koifman; Gulnar Azevedo E Silva; Silvia Francisci; Mariano Santaquilani; Arduino Verdecchia; Hans H Storm; John L Young
Journal:  Lancet Oncol       Date:  2008-07-17       Impact factor: 41.316

8.  A refined comorbidity measurement algorithm for claims-based studies of breast, prostate, colorectal, and lung cancer patients.

Authors:  Carrie N Klabunde; Julie M Legler; Joan L Warren; Laura-Mae Baldwin; Deborah Schrag
Journal:  Ann Epidemiol       Date:  2007-05-25       Impact factor: 3.797

9.  The Cancer Survival Query System: making survival estimates from the Surveillance, Epidemiology, and End Results program more timely and relevant for recently diagnosed patients.

Authors:  Eric J Feuer; Minjung Lee; Angela B Mariotto; Kathy A Cronin; Steve Scoppa; David F Penson; Mark Hachey; Laurie Cynkin; Ginger A Carter; David Campbell; Antoinette Percy-Laurry; Zhaohui Zou; Deborah Schrag; Benjamin F Hankey
Journal:  Cancer       Date:  2012-05-08       Impact factor: 6.860

10.  Life tables for world-wide comparison of relative survival for cancer (CONCORD study).

Authors:  Paolo Baili; Andrea Micheli; Roberta De Angelis; Hannah K Weir; Silvia Francisci; Mariano Santaquilani; Timo Hakulinen; Manuela Quaresmas; Michel P Coleman
Journal:  Tumori       Date:  2008 Sep-Oct
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  34 in total

Review 1.  Drug resistance in castration resistant prostate cancer: resistance mechanisms and emerging treatment strategies.

Authors:  Cameron M Armstrong; Allen C Gao
Journal:  Am J Clin Exp Urol       Date:  2015-08-08

2.  Predicting Individualized Postoperative Survival for Stage II/III Colon Cancer Using a Mobile Application Derived from the National Cancer Data Base.

Authors:  Emmanuel Gabriel; Kristopher Attwood; Pragatheeshwar Thirunavukarasu; Eisar Al-Sukhni; Patrick Boland; Steven Nurkin
Journal:  J Am Coll Surg       Date:  2015-12-23       Impact factor: 6.113

3.  Time-varying survival effects for squamous cell carcinomas at oropharyngeal and nonoropharyngeal head and neck sites in the United States, 1973-2015.

Authors:  Andrew F Brouwer; Kevin He; Steven B Chinn; Alison M Mondul; Christina H Chapman; Marc D Ryser; Mousumi Banerjee; Marisa C Eisenberg; Rafael Meza; Jeremy M G Taylor
Journal:  Cancer       Date:  2020-09-05       Impact factor: 6.860

4.  Cause-specific mortality among Medicare beneficiaries with newly diagnosed non-Hodgkin lymphoma subtypes.

Authors:  Laura L Hester; Steven I Park; William A Wood; Til Stürmer; M Alan Brookhart; Jennifer L Lund
Journal:  Cancer       Date:  2018-12-11       Impact factor: 6.860

5.  Cancer survival: an overview of measures, uses, and interpretation.

Authors:  Angela B Mariotto; Anne-Michelle Noone; Nadia Howlader; Hyunsoon Cho; Gretchen E Keel; Jessica Garshell; Steven Woloshin; Lisa M Schwartz
Journal:  J Natl Cancer Inst Monogr       Date:  2014-11

6.  The impact of state-specific life tables on relative survival.

Authors:  Antoinette M Stroup; Hyunsoon Cho; Steve M Scoppa; Hannah K Weir; Angela B Mariotto
Journal:  J Natl Cancer Inst Monogr       Date:  2014-11

7.  The Surveillance, Epidemiology, and End Results Cancer Survival Calculator SEER*CSC: validation in a managed care setting.

Authors:  Eric J Feuer; Borsika A Rabin; Zhaohui Zou; Zhuoqiao Wang; Xiaoqin Xiong; Jennifer L Ellis; John F Steiner; Laurie Cynkin; Larissa Nekhlyudov; Elizabeth Bayliss; Benjamin F Hankey
Journal:  J Natl Cancer Inst Monogr       Date:  2014-11

8.  Misclassification of the actual causes of death and its impact on analysis: A case study in non-small cell lung cancer.

Authors:  Kay See Tan
Journal:  Lung Cancer       Date:  2019-05-16       Impact factor: 5.705

9.  Anticipating the "Silver Tsunami": Prevalence Trajectories and Comorbidity Burden among Older Cancer Survivors in the United States.

Authors:  Shirley M Bluethmann; Angela B Mariotto; Julia H Rowland
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2016-07       Impact factor: 4.254

10.  Associations of Oral α-, β-, and γ-Human Papillomavirus Types With Risk of Incident Head and Neck Cancer.

Authors:  Ilir Agalliu; Susan Gapstur; Zigui Chen; Tao Wang; Rebecca L Anderson; Lauren Teras; Aimée R Kreimer; Richard B Hayes; Neal D Freedman; Robert D Burk
Journal:  JAMA Oncol       Date:  2016-05-01       Impact factor: 31.777

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