An optimal posttreatment surveillance strategy for cancer survivors based on an individualized risk-based approach.
Nat Commun
; 11(1): 3872, 2020 08 03.
Article
em En
| MEDLINE
| ID: mdl-32747627
ABSTRACT
The optimal post-treatment surveillance strategy that can detect early recurrence of a cancer within limited visits remains unexplored. Here we adopt nasopharyngeal carcinoma as the study model to establish an approach to surveillance that balances the effectiveness of disease detection versus costs. A total of 7,043 newly-diagnosed patients are grouped according to a clinic-molecular risk grouping system. We use a random survival forest model to simulate the monthly probability of disease recurrence, and thereby establish risk-based surveillance arrangements that can maximize the efficacy of recurrence detection per visit. Markov decision-analytic models further validate that the risk-based surveillance outperforms the control strategies and is the most cost-effective. These results are confirmed in an external validation cohort. Finally, we recommend the risk-based surveillance arrangement which requires 10, 11, 13 and 14 visits for group I to IV. Our surveillance strategies might pave the way for individualized and economic surveillance for cancer survivors.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Nasofaríngeas
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Sobreviventes de Câncer
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Carcinoma Nasofaríngeo
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Monitorização Fisiológica
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article