Page 15 - Risk quantification and modification in older patients with colorectal cancer

information should include not only adverse events but also functional outcomes and quality of life after treatment, as this information is especially relevant to older patients. Providing prognostic information can also be used to identify high-risk populations to indicate interventions aimed at improving surgical outcomes.
Risk modification
In CRC care, perioperative interventions such as Enhanced Recovery After Surgery (ERAS) and laparoscopic surgery, have been shown to be beneficial to older patients.52,53 Several studies have addressed the effects of prehabilitation before surgery aimed to increase resilience54,55 and early discharge to a rehabilitation centre aimed to reduce the adverse effects of a hospital stay.56 In the majority of younger patients, prehabilitation before CRC surgery positively influenced physical performance,55,57-59 but the impact on postoperative complications was absent.60 Also, in patients scheduled for thoracic surgery, prehabilitation has shown to reduce complication rates and shorten hospital stay.61 However, prehabilitation studies in older CRC patients are scarce and results are inconsistent.58 There is also a lack of studies that investigated optimal patient selection for prehabilitation. However, information collected from a (C)GA might be of aid.
In patients planned for cancer treatment, CGA can be used to direct non- oncological interventions including nutritional, social and psychological support, and medication optimisation. Such non-oncological interventions are proposed in up to 70% of patients referred for CGA. Therefore, geriatric screening and assessment are recommended as part of standard oncological workup.62 Thus far, the usefulness of oncogeriatric care and interventions on outcomes of CRC surgery including mortality, complications, quality of life and physical functioning is not clear.
Aim and thesis outline
This thesis aims to investigate which older patients with CRC are at risk of poor surgical outcomes. Existing prediction tools are explored and evaluated, and predictive patient characteristics are studied in a real life cohort (Part I). In addition,
Introduction and thesis outline
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