PS1517 MILD COGNITIVE IMPAIRMENT, HYPOALBUMINEMIA, HIGH CRP AND GASTRO-INTESTINAL ULCER: 4 MARKERS OF FRAILTY WHICH IDENTIFY OLDER PATIENTS WITH MALIGNANT HEMOPATHIES WHO DON’T BENEFIT FROM CHEMOTHERAPY

Abstract

Background: Areliable frailty score remains needed to better define the unsuspected vulnerable population that does not benefit from chemotherapy. In the literature, three clinical (functional decline, cognitive impairment (CI) and comorbidities) and two biological (low albumin level and high IL-6 level) factors are associated with poor overall survival. Aims: To develop and evaluate a simple clinico-biological tool for the screening of vulnerability and prediction of poor survival in patients (pts) with malignant hemopathies. Methods: 285 pts (65–90yrs) admitted to receive chemotherapy were included in a prospective multicentric Belgian study. Univariate and multivariate Cox proportional hazards models were used to evaluate the value of functional decline, abnormal cognitive function, comorbidities, low albumin and CRP level to predict 1-year survival. A “frailty” score was then developed based on those parameters. This “frailty” score was externally validated in a small cohort of 25 patients (64–93yrs) from a French hematological center. Kaplan-Meier survival estimates were used to compare survival of patients with each score of the frailty scoring. Results: In the Belgian cohort,200pts were evaluable for the clinico-biological screening tool. 83% percent were considered to have a more favorable prognosis. Functional decline was associated with abnormal cognitive function (p < .001) and inflammation (p < .001). Based on previous analyses in the Charlson Comorbidity Index, the gastro-intestinal (GI) ulcer was the strongest prognostic factor (p < .001); the “frailty” score is based on 4 independent predictive factors for poor survival: CI (MMSE<27, n = 62), presence of GI ulcer (n = 29), low albumin level (alb<35 g/L, n = 59) and CRP (CRP≥10 mg/l, n = 81). The population was stratified into 3 groups: “fit” (score = 0–1, n = 137), “vulnerable” (score = 2, n = 36) and “frail” (score = 3–4, n = 27). The one-year survival was 75% in “fit”, 53% in “vulnerable” (HR = 2.26; 95% CI = 1.26–4.04; p = .006) and 33% in “frail” pts (HR = 4.36; 95% CI = 2.45–7.75; p < .001). In the validation cohort, the one-year survival was 78% in “fit” (n = 9), 50% in “vulnerable” (n = 6, HR = 2.03; 95% CI = 0.34–12.1; P = .44) and 40% in “frail” patients (n = 10, HR = 4.12; 95% CI = 1.39–32.41; P = .018). The median survival was in the “frail” group was under 6 months in both cohorts (4 months in the Belgian cohort and 5.6 months in the validation cohort). Summary/Conclusion: In this (selected) population of “clinically fit pts” from independent centers, referred to receive chemotherapy for malignant hemopathies, this frailty score helps the clinician to predict a poor outcome. Though the number of pts in the validation cohort was relatively small, the predictive performance to identify a poor prognostic group of pts is confirmed. This frailty score detects unsuspected frailty in pts who don’t benefit from chemotherapy. Ongoing prospective analyses in a larger cohort of malignant hemopathies will be updated to validate the reliability of this score.