Predicting Outcomes in Older Patients With Cancer


Key Points

  • All four frailty models showed good discrimination for risk of 1-year mortality in older patients with various cancers.
  • All frailty classifications showed good discrimination for risk of 6-month unscheduled hospital admission.

In the French ELCAPA14 study reported in the Journal of Clinical Oncology, Ferrat et al found that four frailty classifications performed well in predicting outcomes in a cohort of patients aged ≥ 70 years with various cancers.

Study Details

The study involved 763 in- or outpatients with hematologic or solid malignancies enrolled in the ELCAPA prospective cohort between 2007 and 2012 from two French hospitals who had data available for each of the four frailty classifications examined: Balducci classification, International Society of Geriatric Oncology (SIOG) 1, SIOG2, and a latent class typology. Outcomes examined were 1-year mortality and 6-month unscheduled hospital admissions. Reference categories were "fit" (vs vulnerable or frail or too sick [SIOG1]) for the Balducci and SIOG1 and SIOG2 classifications and "relatively healthy" (vs 3 categories of poorer health) for the latent class typology classification.

Discriminative Performance

All four models showed good discrimination for 1-year mortality, with C-index values ranging from 0.74 to 0.77 (SIOG1). For 6-month unscheduled admissions, discrimination was good with all four classifications (C-index ≥ 0.70 for each), with similar discrimination for all models. For mortality, C-index values indicated very good discrimination for mortality (0.82–0.84) and hospital admission (0.79–0.80) among patients without metastases but moderate discrimination for both (0.65–0.69) among patients with metastases. For classification into three (fit, vulnerable, or frail) or two categories (fit vs vulnerable or frail; fit or vulnerable vs frail), agreement among the classifications ranged from very poor (κ ≤ 0.20) to good (0.60 < κ ≤ 0.80), with the best agreement being found between the SIOG1 and latent class typology models and between the SIOG1 and Balducci models.

The investigators concluded: “These four frailty classifications have good prognostic performance among older in- and outpatients with various cancers. They may prove useful in decision making about cancer treatments and geriatric interventions and/or in stratifying older patients with cancer in clinical trials.”

The study was supported by the Institut National du Cancer and Canceropôle Ile-de-France.

Emilie Ferrat, MD, PhD, of the University Paris-Est Créteil, is the corresponding author of the Journal of Clinical Oncology article.

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