Patients with Acute Myeloid Leukemia Admitted to Intensive Care Units: Outcome Analysis and Risk Prediction

Approximately 13% of patients with Acute Myeloid Leukemia (AML) require Intensive Care Unit (ICU) treatment. However, the decision to admit an AML patient to the ICU often poses a clinical quandary. The treating physician needs to consider the patient’s wishes and needs to collaborate with other specialists. Often the decision to finally refer the patient to ICU is loosely based on established scores (e.g. SOFA, LOD, APACHE II, SAPS II) and these scores may not be the most appropriate tool for assessing AML patients.

M. Pohlen et al. retrospectively analyzed data from 451 adults with AML treated in ICU. The objective was to establish and validate risk factors associated with mortality during and after ICU treatment based on a large and multicenter cohort, as well as to establish potential risk scores. This is the largest AML cohort analyzed within this clinical setting to date; their results were published in PLOS in August 2016.

Their key findings were:

The authors stratified the ICU survivors into three risk groups according to the risk score calculated using a special formula which demonstrated striking differences in survival after ICU discharge. There were two cohorts of data described; the training cohort and the validation cohort.

The Training Cohort:

• The projected 3-year survival of this cohort from the time of ICU discharge was 64% (95% CI: 51–77%) after a median follow-up of 1.6 years
• Patients with the lowest risk (X values <0.23, n = 15) displayed 1-year survival after ICU discharge of 100%
• Patients with intermediate risk (X values between 0.23 and 2.33, n = 34) exhibited 1-year survival of 82% (95% CI: 68–97%)
• Patients with the highest risk (X value >2.34, n = 30) exhibited 1-year survival of 42% (95% CI: 22–63%) (Fig 1A)

The Validation Cohort:

• • For patients with the lowest risk (n=59), 1-year survival after ICU discharge was 69% (95% CI: 55–81%)
  • For the intermediate risk patients (n=131), 1-year survival after ICU discharge was 51% (95% CI: 41–60%)
  • For the highest risk patients (n=42), 1-year survival after ICU discharge was 19% (95% CI: 4–33%)  (Fig 1B)

Figure 1: Correlation of predicted survival rate after ICU (Intensive Care Unit) discharge with overall survival. Patients were grouped according to their probability of survival and the corresponding Kaplan-Meier estimates. (A) Overall survival for patients in the training cohort. (B) Overall survival for patients in the validation group.

Conclusion

In conclusion, clinicians often assume that there will be high mortality for AML referred to ICU. However, the data by Pohlen et al. have identified useful risk predictor tools. They have developed two scores which could distinguish between survival differences both in the ICU as well as after ICU discharge. ELN low risk demonstrated a significant correlation between survival after ICU discharge, whereas ELN high risk only showed borderline significance.

Abstract

Background

This retrospective, multicenter study aimed to reveal risk predictors for mortality in the intensive care unit (ICU) as well as survival after ICU discharge in patients with acute myeloid leukemia (AML) requiring treatment in the ICU.

Methods and Results

Multivariate analysis of data for 187 adults with AML treated in the ICU in one institution revealed the following as independent prognostic factors for death in the ICU: arterial oxygen partial pressure below 72 mmHg, active AML and systemic inflammatory response syndrome upon ICU admission, and need for hemodialysis and mechanical ventilation in the ICU. Based on these variables, we developed an ICU mortality score and validated the score in an independent cohort of 264 patients treated in the ICU in three additional tertiary hospitals. Compared with the Simplified Acute Physiology Score (SAPS) II, the Logistic Organ Dysfunction (LOD) score, and the Sequential Organ Failure Assessment (SOFA) score, our score yielded a better prediction of ICU mortality in the receiver operator characteristics (ROC) analysis (AUC = 0.913 vs. AUC = 0.710 [SAPS II], AUC = 0.708 [LOD], and 0.770 [SOFA] in the training cohort; AUC = 0.841 for the developed score vs. AUC = 0.730 [SAPSII], AUC = 0.773 [LOD], and 0.783 [SOFA] in the validation cohort). Factors predicting decreased survival after ICU discharge were as follows: relapse or refractory disease, previous allogeneic stem cell transplantation, time between hospital admission and ICU admission, time spent in ICU, impaired diuresis, Glasgow Coma Scale <8 and hematocrit of ≥25% at ICU admission. Based on these factors, an ICU survival score was created and used for risk stratification into three risk groups. This stratification discriminated distinct survival rates after ICU discharge.

Conclusions

Our data emphasize that although individual risks differ widely depending on the patient and disease status, a substantial portion of critically ill patients with AML benefit from intensive care.