Literature DB >> 18264781

Hazard regression model and cure rate model in colon cancer relative survival trends: are they telling the same story?

Theodora Bejan-Angoulvant1, Anne-Marie Bouvier, Nadine Bossard, Aurelien Belot, Valérie Jooste, Guy Launoy, Laurent Remontet.   

Abstract

Hazard regression models and cure rate models can be advantageously used in cancer relative survival analysis. We explored the advantages and limits of these two models in colon cancer and focused on the prognostic impact of the year of diagnosis on survival according to the TNM stage at diagnosis. The analysis concerned 9,998 patients from three French registries. In the hazard regression model, the baseline excess death hazard and the time-dependent effects of covariates were modelled using regression splines. The cure rate model estimated the proportion of 'cured' patients and the excess death hazard in 'non-cured' patients. The effects of year of diagnosis on these parameters were estimated for each TNM cancer stage. With the hazard regression model, the excess death hazard decreased significantly with more recent years of diagnoses (hazard ratio, HR 0.97 in stage III and 0.98 in stage IV, P < 0.001). In these advanced stages, this favourable effect was limited to the first years of follow-up. With the cure rate model, recent years of diagnoses were significantly associated with longer survivals in 'non-cured' patients with advanced stages (HR 0.95 in stage III and 0.97 in stage IV, P < 0.001) but had no significant effect on cure (odds ratio, OR 0.99 in stages III and IV, P > 0.5). The two models were complementary and concordant in estimating colon cancer survival and the effects of covariates. They provided two different points of view of the same phenomenon: recent years of diagnosis had a favourable effect on survival, but not on cure.

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Year:  2008        PMID: 18264781     DOI: 10.1007/s10654-008-9226-6

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  22 in total

1.  A relative survival regression model using B-spline functions to model non-proportional hazards.

Authors:  Roch Giorgi; Michal Abrahamowicz; Catherine Quantin; Philippe Bolard; Jacques Esteve; Joanny Gouvernet; Jean Faivre
Journal:  Stat Med       Date:  2003-09-15       Impact factor: 2.373

2.  The relative survival rate: a statistical methodology.

Authors:  F EDERER; L M AXTELL; S J CUTLER
Journal:  Natl Cancer Inst Monogr       Date:  1961-09

3.  Improvement in colorectal cancer survival: a population-based study.

Authors:  Emmanuel Mitry; Anne-Marie Bouvier; Jacques Esteve; Jean Faivre
Journal:  Eur J Cancer       Date:  2005-09-01       Impact factor: 9.162

4.  The cure for colon cancer: results from the EUROCARE study.

Authors:  A Verdecchia; R De Angelis; R Capocaccia; M Sant; A Micheli; G Gatta; F Berrino
Journal:  Int J Cancer       Date:  1998-07-29       Impact factor: 7.396

5.  Relative survival and the estimation of net survival: elements for further discussion.

Authors:  J Estève; E Benhamou; M Croasdale; L Raymond
Journal:  Stat Med       Date:  1990-05       Impact factor: 2.373

6.  Cancer incidence and mortality in France over the period 1978-2000.

Authors:  L Remontet; J Estève; A-M Bouvier; P Grosclaude; G Launoy; F Menegoz; C Exbrayat; B Tretare; P-M Carli; A-V Guizard; X Troussard; P Bercelli; M Colonna; J-M Halna; G Hedelin; J Macé-Lesec'h; J Peng; A Buemi; M Velten; E Jougla; P Arveux; L Le Bodic; E Michel; M Sauvage; C Schvartz; J Faivre
Journal:  Rev Epidemiol Sante Publique       Date:  2003-02       Impact factor: 1.019

7.  The use of mixture models for the analysis of survival data with long-term survivors.

Authors:  V T Farewell
Journal:  Biometrics       Date:  1982-12       Impact factor: 2.571

8.  Cure model analysis in cancer: an application to data from the Children's Cancer Group.

Authors:  Richard Sposto
Journal:  Stat Med       Date:  2002-01-30       Impact factor: 2.373

9.  Survival for colon and rectal cancer in a population-based cancer registry.

Authors:  L Roncucci; R Fante; L Losi; C Di Gregorio; A Micheli; P Benatti; N Madenis; D Ganazzi; M T Cassinadri; P Lauriola; M Ponz de Leon
Journal:  Eur J Cancer       Date:  1996-02       Impact factor: 9.162

10.  Colon cancer in France: evidence for improvement in management and survival.

Authors:  C Faivre-Finn; A-M Bouvier-Benhamiche; J M Phelip; S Manfredi; V Dancourt; J Faivre
Journal:  Gut       Date:  2002-07       Impact factor: 23.059

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  3 in total

1.  Statistical Issues and Lessons Learned From COVID-19 Clinical Trials With Lopinavir-Ritonavir and Remdesivir.

Authors:  Guosheng Yin; Chenyang Zhang; Huaqing Jin
Journal:  JMIR Public Health Surveill       Date:  2020-07-10

2.  A genome-wide association study identifies single nucleotide polymorphisms associated with time-to-metastasis in colorectal cancer.

Authors:  Michelle E Penney; Patrick S Parfrey; Sevtap Savas; Yildiz E Yilmaz
Journal:  BMC Cancer       Date:  2019-02-09       Impact factor: 4.430

3.  XRCC3 Thr241Met and TYMS variable number tandem repeat polymorphisms are associated with time-to-metastasis in colorectal cancer.

Authors:  Yanjing He; Michelle E Penney; Amit A Negandhi; Patrick S Parfrey; Sevtap Savas; Yildiz E Yilmaz
Journal:  PLoS One       Date:  2018-02-02       Impact factor: 3.240

  3 in total

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