- ICH GCP
- Registr klinických studií v USA
- Klinická studie NCT02894801
Multistate Relative Survival Model (MRS)
Multistate Relative Survival Modeling of Colorectal Cancer Progression and Mortality
Colorectal cancer (CRC) has high incidence and is associated with high case fatality. In France, the 5-year survival, pooled across all cancer stages at diagnosis, ranges from 57% in men to 60% in women. About one third of patients diagnosed with CRC will develop a metachronous recurrence during the following years. It is of paramount importance to accurately identify factors associated with the increased risk of progression and death, in order to develop effective follow-up and treatment strategies. However, to accurately assess the role of patients' specific characteristics in the progression of cancer several methodological challenges need to be overcome.
One difficulty, common to prognostic studies of cancer, concerns the need to separate the effects of prognostic factors on different clinical endpoints, such as disease recurrence vs recurrence-free death. Another difficulty, encountered in prognostic studies, is that the cause of death is not available or not accurately coded. Yet, some patients are likely to die of causes not related to the disease of primary interest, especially in cancers with longer survival and in those that affect older subjects. Until recently, the existing statistical methodology was not able to simultaneously, deal with both difficulties, i.e. to account for (i) possibly different effects of prognostic factors on death vs recurrence, and (ii) unknown causes of death. However, this challenge has been addressed by the recent development of the Markov relative survival model (MRS) , which extends the Markov multi-state model to incorporate relative survival modelling. Simulations demonstrate that MRS is able to accurately estimate different effects of prognostic factors on the risk of each of several events, including separate effects on disease-specific vs other causes of death. To date, the MRS had not been applied in clinical or epidemiological studies.
The aim of this study was to assess the potential advantages of the new multi-state relative survival model (MRS), proposed by Huszti et al. (2012), in a prognostic cancer study. To this end, we compared the MRS results with those obtained with two more conventional analyses, based on Cox's proportional hazards model, and the multi-state Markov model proposed by Alioum and Commenges (2001). The three models were applied to explore the impact of prognostic factors on cancer-specific mortality and recurrence, in a large population-based French registry of colorectal cancer, with up to 25 years of follow-up.
Přehled studie
Postavení
Podmínky
Typ studie
Zápis (Aktuální)
Kontakty a umístění
Studijní místa
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Dijon, Francie, 21079
- CHU Dijon Bourgogne
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Kritéria účasti
Kritéria způsobilosti
Věk způsobilý ke studiu
- Dítě
- Dospělý
- Starší dospělý
Přijímá zdravé dobrovolníky
Pohlaví způsobilá ke studiu
Metoda odběru vzorků
Studijní populace
Popis
Inclusion Criteria:
patient with primary digestive cancer between 1985 and 2000, TNM I-III, resected for cure, residing in Burgundy or Calvados, France
Exclusion Criteria:
metastatic cancer, non adenocarcinoma, recurrence within 6 month
Studijní plán
Jak je studie koncipována?
Detaily designu
Co je měření studie?
Primární výstupní opatření
Měření výsledku |
Časové okno |
---|---|
death due to cancer
Časové okno: 10 years after resection
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10 years after resection
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death due to recurrence
Časové okno: 10 years after resection
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10 years after resection
|
Spolupracovníci a vyšetřovatelé
Termíny studijních záznamů
Hlavní termíny studia
Začátek studia
Primární dokončení (Aktuální)
Termíny zápisu do studia
První předloženo
První předloženo, které splnilo kritéria kontroly kvality
První zveřejněno (Odhad)
Aktualizace studijních záznamů
Poslední zveřejněná aktualizace (Odhad)
Odeslaná poslední aktualizace, která splnila kritéria kontroly kvality
Naposledy ověřeno
Více informací
Termíny související s touto studií
Další relevantní podmínky MeSH
Další identifikační čísla studie
- PIOC 2015
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