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Evidence-based appraisal of the upfront treatment for unresectable metastatic colorectal cancer patients.


ABSTRACT: Colorectal cancer (CRC) is a significant health problem, with around 1 million new cases and 500000 deaths every year worldwide. Over the last two decades, the use of novel therapies and more complex treatment strategies have contributed to progressively increase the median survival of patients with unresectable advanced CRC up to approximately 30 mo. The availability of additional therapeutic options, however, has created new challenges and generated more complicated treatment algorithms. Moreover, several clinically important points are still in debate in first-line, such as the optimal treatment intensity, the most appropriate maintenance strategy, the preferred biologic to be used upfront in patients with KRAS wild-type CRC, and the need for more detailed information on tumor biology. In this moving landscape, this review analyses why the first-line treatment decision is crucial and how the choice may impact on further treatment lines. In addition, it focuses on results of major phase III randomized trials.

SUBMITTER: Aprile G 

PROVIDER: S-EPMC3870493 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Evidence-based appraisal of the upfront treatment for unresectable metastatic colorectal cancer patients.

Aprile Giuseppe G   Lutrino Stefania Eufemia SE   Ferrari Laura L   Casagrande Mariaelena M   Bonotto Marta M   Ongaro Elena E   Puglisi Fabio F  

World journal of gastroenterology 20131201 46


Colorectal cancer (CRC) is a significant health problem, with around 1 million new cases and 500000 deaths every year worldwide. Over the last two decades, the use of novel therapies and more complex treatment strategies have contributed to progressively increase the median survival of patients with unresectable advanced CRC up to approximately 30 mo. The availability of additional therapeutic options, however, has created new challenges and generated more complicated treatment algorithms. Moreo  ...[more]

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