ABSTRACT
Objetivo: Mejorar el rendimiento de la escala Acute Physiology and Chronic Health Evaluation (APACHE) II para la predicción de muerte hospitalaria en pacientes críticos con cáncer. Materiales y métodos: Estudio prospectivo de 522 pacientes con cáncer sólido admitidos en UCI. Se creó la «escala APACHE II para pacientes con cáncer sólido» (escala APACHE IIPCC); se adicionaron variables típicas del paciente oncológico crítico a la escala APACHE II general. Se evaluó la calibración (prueba de Hosmer-Lemeshow [H-L]) y discriminación (área bajo la curva de las características operativas del receptor [ACOR]). Se utilizó la mejora en la discriminación integrada (IDI), mejora neta en la reclasificación (NRI; 20% como valor de corte en el riesgo de muerte) y NRI cuantitativo (cNRI) para evaluar la mejora en la predicción de muerte hospitalaria con el nuevo modelo. Resultados: La mortalidad hospitalaria fue del 13%. La discriminación fue superior con la escala APACHE IICCP (ACOR = 0,91 [IC del 95% 0,87-0,94; p < 0,0001]) comparado con la escala APACHE II general (ACOR = 0,62 [IC del 95% 0,54-0,70; p = 0,002]). La calibración fue mejor con la escala APACHE IICCP (H-L p = 0,267 vs. p = 0,001). En el análisis de reclasificación se observó una mejora en la predicción de muerte con la escala APACHE IICCP (IDI = 0,2994 [p < 0,0001]; cNRI = 134,3% [IC del 95% 108,8-159,8%; p < 0,0001]; NRI = 41,5% [IC del 95% 23,7-59,3%; p < 0,0001]). Conclusiones: La escala APACHE IICCP fue superior a la escala APACHE II general en la predicción de muerte en pacientes críticos con cáncer sólido. Se requieren otros estudios que validen este nuevo modelo predictivo
Objective: To improve the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) II model for predicting hospital mortality in critically ill cancer patients. Materials and methods: This was a prospective cohort study of 522 patients admitted to ICU with a solid tumor. We developed the "APACHE II score for critically ill patients with a solid tumor" (APACHE IICCP score), in which typical variables of critically ill cancer patients were added to general APACHE II score. Calibration and discrimination were evaluated by Hosmer-Lemeshow test (H-L) and area under receiver operating characteristic curve (AROC), respectively. The improvement in predicting hospital mortality with the new model was assessed using a reclassification analysis by integrated discrimination improvement (IDI), net reclassification improvement (NRI; cut-off point of 20% in risk of death) and quantitative NRI (qNRI). Results: The hospital mortality rate was 13%. Discrimination was superior for APACHE IICCP score (AROC=0.91 [95% CI 0.87-0.94; P<.0001]) compared to general APACHE II score (AROC=0.62 [95% CI 0.54-0.70; P=.002]). Calibration was better using APACHE IICCP score (H-L; P=.267 vs. P=.001). In reclassification analysis, an improved mortality prediction was observed with APACHE IICCP score (IDI=0.2994 [P<.0001]; total qNRI=134.3% [95% CI 108.8-159.8%; P<.0001]; total NRI=41.5% [95% CI 23.7-59.3%; P<.0001]). Conclusions: The performance of APACHE IICCP score was superior to that observed for general APACHE II score in predicting mortality in critically ill patients with a solid tumor. Other studies validating this new predictive model are required
Subject(s)
Humans , Male , Female , Middle Aged , Aged , Critical Illness/classification , Severity of Illness Index , Response Evaluation Criteria in Solid Tumors , APACHE , Neoplasms/classification , Prospective Studies , Hospital Mortality , Risk Adjustment/methodsABSTRACT
OBJECTIVE: To improve the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) II model for predicting hospital mortality in critically ill cancer patients. MATERIALS AND METHODS: This was a prospective cohort study of 522 patients admitted to ICU with a solid tumor. We developed the "APACHE II score for critically ill patients with a solid tumor" (APACHE IICCP score), in which typical variables of critically ill cancer patients were added to general APACHE II score. Calibration and discrimination were evaluated by Hosmer-Lemeshow test (H-L) and area under receiver operating characteristic curve (AROC), respectively. The improvement in predicting hospital mortality with the new model was assessed using a reclassification analysis by integrated discrimination improvement (IDI), net reclassification improvement (NRI; cut-off point of 20% in risk of death) and quantitative NRI (qNRI). RESULTS: The hospital mortality rate was 13%. Discrimination was superior for APACHE IICCP score (AROC=0.91 [95% CI 0.87-0.94; P<.0001]) compared to general APACHE II score (AROC=0.62 [95% CI 0.54-0.70; P=.002]). Calibration was better using APACHE IICCP score (H-L; P=.267 vs. P=.001). In reclassification analysis, an improved mortality prediction was observed with APACHE IICCP score (IDI=0.2994 [P<.0001]; total qNRI=134.3% [95% CI 108.8-159.8%; P<.0001]; total NRI=41.5% [95% CI 23.7-59.3%; P<.0001]). CONCLUSIONS: The performance of APACHE IICCP score was superior to that observed for general APACHE II score in predicting mortality in critically ill patients with a solid tumor. Other studies validating this new predictive model are required.
