Literature DB >> 16249212

Life expectancy as an indicator of outcome in follow-up of population-based cancer registries: the example of childhood leukemia.

S Viscomi1, G Pastore, E Dama, L Zuccolo, N Pearce, F Merletti, C Magnani.   

Abstract

BACKGROUND: Survival analysis is a standard methodology to assess progress in oncology disease treatment. However, survival analysis commonly only measures survival during the treatment period (and the period immediately afterwards), and does not provide an estimate of life expectancy, which is often of more interest to patients and to health policy makers. In this paper we propose a method to estimate childhood acute lymphoblastic leukemia (ALL) life expectancy through the integration of traditional survival analysis and life expectancy tables. PATIENTS AND METHODS: The study included 305 incident cases registered by the Childhood Cancer Registry of Piedmont in 1979-1991. Vital status on 30 June 2004 was known for 304 cases. Survival analyses were carried out using the Kaplan-Meier method and the Gompertz model, according to the time period of diagnosis and gender.
RESULTS: Cumulative survival at 5 years increased from 58.6% (95% CI 48.9-68.3) for cases diagnosed in March 1979-July 1982 to 79.1% (95% CI 70.8-87.5) in March 1987-February 1991 (P = 0.002). Average life expectancy increased from 46.1 years for boys and 42.6 years for girls diagnosed in March 1979-July 1982 to 58.3 and 69.1, respectively, in March 1987-February 1991.
CONCLUSIONS: These analyses show an improvement over the time period of diagnosis of life expectancy for children with ALL.

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Mesh:

Year:  2005        PMID: 16249212     DOI: 10.1093/annonc/mdj050

Source DB:  PubMed          Journal:  Ann Oncol        ISSN: 0923-7534            Impact factor:   32.976


  6 in total

1.  Survival extrapolation in the presence of cause specific hazards.

Authors:  Tatiana Benaglia; Christopher H Jackson; Linda D Sharples
Journal:  Stat Med       Date:  2014-11-20       Impact factor: 2.373

2.  Application of Parametric Models to a Survival Analysis of Hemodialysis Patients.

Authors:  Maryam Montaseri; Jamshid Yazdani Charati; Fateme Espahbodi
Journal:  Nephrourol Mon       Date:  2016-09-13

3.  Illustration of different modelling assumptions for estimation of loss in expectation of life due to cancer.

Authors:  Therese M-L Andersson; Mark J Rutherford; Paul C Lambert
Journal:  BMC Med Res Methodol       Date:  2019-07-09       Impact factor: 4.615

4.  Life expectancy and cancer survival in Oncosalud: outcomes over a 15-year period in a Peruvian private institution.

Authors:  Christian Colonio; Luciana Lecman; Joseph A Pinto; Carlos Vallejos; Luis Pinillos
Journal:  Ecancermedicalscience       Date:  2021-12-16

5.  Narrative review of women's health in Iran: challenges and successes.

Authors:  Hassan Joulaei; Najmeh Maharlouei; Kamran Bagheri Lankarani; Alireza Razzaghi; Maryam Akbari
Journal:  Int J Equity Health       Date:  2016-02-16

Review 6.  Extrapolating Survival from Randomized Trials Using External Data: A Review of Methods.

Authors:  Christopher Jackson; John Stevens; Shijie Ren; Nick Latimer; Laura Bojke; Andrea Manca; Linda Sharples
Journal:  Med Decis Making       Date:  2016-07-10       Impact factor: 2.583

  6 in total

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