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1000
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Abstract/Summary
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Background!#!Physical training is recommended in various national and international guidelines for patients with cancer. Observational studies have shown that physical activity leads to reduced recurrence and mortality rates by 20-40% in colorectal, breast, and prostate cancer. Despite existing evidence, a systematic care structure is still lacking. The primary aim of this study is to implement and evaluate an online training platform to strengthen physical performance and patient empowerment after cancer surgery.!##!Methods!#!The evaluation will be conducted as a prospective multicenter randomized controlled trial with three subgroups (colorectal-, breast-, and prostate cancer). Each group will include 100 patients (total 300 patients including dropouts; clinical stages T1-3 and/or N+; M0 after surgery intervention) and the primary endpoint (13% increase in the maximal oxygen consumption during exercise) will be examined. The intervention group will receive a 6-month home-based online training (2-3 times per week strength-endurance training using video presentations), bidirectional activity feedback information, online communication, and online counseling. The control group (usual care) will be advised lifestyle improvement. In-hospital testing will be performed before, during, and after the intervention. In addition to cardiopulmonary capacity, tumor specific diagnostics (liquid biopsy, depression and fatigue assessment, metabolic and endothelial screening) will be applied.!##!Discussion!#!Due to the increasing incidence of cancer, associated with considerable mortality, morbidity and impaired quality of life, there is an imperative requirement for improved cancer care, of which structured physical training may become an integral component.!##!Trial registration!#!DRKS-ID: DRKS00020499 ; Registered 17 March 2020.
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1000
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Hinweis
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DeepGreen-ID: fe162c9e6cef423eb7e44ccbfa1de5bf ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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