First recommendations are released from the ESMO/SIOG Cancer in the Elderly Working Group
As the global population is aging, it is expected that older adults will constitute a growing proportion of new cancer cases in the next decades (CA Cancer J Clin 2021; 71 (3): 209-249). However, vulnerabilities associated with older age may affect the quality of the care they receive, and many patients over 60 years old are still overtreated or undertreated (J Clin Oncol. 2018 Aug 1;36(22):2326-2347). With a position paper just released on ESMO Open, the ESMO/ International Society of Geriatric Oncology (SIOG) Cancer in the Elderly Working Group reaffirms that a geriatric assessment and management (GAM) plays a crucial role in delivering patient-centered and personalised care to geriatric patients with cancer. (Article in press)
By reviewing the recent literature in the field and discussing the results from selected randomised trials, the group developed a set of recommendations to assess and adequately treat this population, as follows:
- GAM should be implemented in patients aged ≥70 years (and ≥65 years when possible) being considered for cancer-directed treatments, especially systemic treatments.
- GAM should be performed as early as possible prior to treatment initiation, and when possible, prior to finalisation of the treatment plan.
- In settings where GAM cannot be performed for all patients, use validated screening tools to identify those who are likely to benefit from subsequent GAM.
- Models of GAM delivery needs to be tailored to the availability of local resources, settings (e.g., academic cancer centers vs community oncology practices), and staff (e.g., geriatricians or geriatric oncologists, and other allied healthcare professionals).
- Utilise the Cancer and Aging Research Group (CARG) or Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) tools to estimate chemotherapy toxicity in older patients with cancer.
As reported in the paper, further research in the field is needed, including comparing models of GAM in specific cancer types, exploring their application during and after treatments, integrating novel or combined endpoints in clinical trials of GAM, such as both objective outcomes and patient-reported outcomes.