Abstract 1872P
Background
The mortality rate among cancer patients receiving systemic therapy is high, requiring the need for predictors of mortality. This study aimed to evaluate the accuracy of PROMISE (Mirallas et al., ASCO 2022), Gustave Roussy Immune Score (GRIm), and CRP-Triglyceride-Glucose Index (CTI) scores for predicting 90-day mortality in hospitalized patients.
Methods
Patients hospitalized at Ankara Etlik City Hospital's Medical Oncology Clinic within the last year were retrospectively reviewed. Patients receiving active chemotherapy or who had received chemotherapy in the past 6 months, with stage 3-4 malignancies, and hospitalized unplanned were included. PROMISE, GRIm, and CTI scores were calculated, and their association with 90-day mortality was assessed.
Results
Out of 1109 patients, the 90-day mortality rate stood at 36.8% (n=408). Notably, patients classified as high risk by PROMISE score exhibited a mortality rate of 58.8% (n=362), compared to 18.1% (n=39) and 2.5%(n=7) in the medium and low-risk categories, respectively (p < 0.001). Patients with low-risk PROMISE scores demonstrated a significantly reduced 90-day mortality rate (HR: 0.39, 95% CI: 0.018-0.81, p<0.001). Patients with high GRIm scores had a significantly higher 90-day mortality rate compared to those with low scores (57.8% vs. 12.2%, p<0.001). CTI scoring was feasible in 333 patients. Among patients with high CTI scores, 98 (58.7%) died within the first 90 days, while the 90-day mortality rate was 11.4% in the low CTI score group (p<0.001). In multivariable analysis, high PROMISE score (HR: 1.98, 95% CI: 1.03-3.80, p=0.039), high CTI score (HR:1.73, 95% CI: 1.01-2.95, p=0.043), ECOG performance score of 2 or higher (HR: 3.15, 95% CI: 1.23-8.04, p=0.016), and progressive disease status (HR: 4.77, 95% CI: 2.00-11.31, p<0.001) were found to be associated with 90-day mortality.
Conclusions
The accuracy of the PROMISE score in predicting 90-day mortality was demonstrated in our study. The PROMISE score holds promise for assisting clinicians in tailoring medical interventions to optimize patient care.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
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Abstract