Clinicians may have doubts about the appropriateness of an ICU admission in patients with a malignancy or a malignancy in their medical history. Reliable literature about long-term mortality and morbidity of patients with a malignancy admitted unplanned to the ICU is essential in order to manage outcome expectations of health care providers, patients and families. We found in our study that a poor functional status as measured by the ECOG performance status, SOFA score at admission and, to a lesser extent, age were independently associated with a poorer short-term and long-term outcome.
Two thirds of the patients with an active malignancy or a malignancy in their medical history die within 2 years after ICU admission. The 2-year mortality of the study population is approximately 1.5 times higher than the 2-year mortality in the population without malignancy. One explanation for this difference could be the weakened condition with a poor ECOG performance status directly after ICU discharge in the study population. The performance status was still reduced at hospital discharge, influencing long-term mortality.
The hospital mortality of our study population was similar to other European literature (44%) (3–5, 24–27). In contrast, the long-term mortality in our study was higher than in other studies (28–34). An explanation may be the difference in case-mix. We included only unplanned ICU admissions, while most other studies included patients with planned ICU admissions as well. Moreover, our study population had a higher SOFA score and received more often organ support.
We found that comfort care was started more often in our study population (35%) than in our population without cancer (20%) and the study population of a specialised Portuguese Cancer institute (13%) (27). Besides differences in case-mix, end-of-life (EoL) decisions could be influenced by many factors, such as religious beliefs, cultural backgrounds, and the ethical climate of the team (35). Consequently, the presence of malignancy or a malignancy in the medical history could influence EoL decisions by clinicians. By starting comfort care, we might spare patients from invasive treatments, such as the insertion of multiple intravenous catheters or prolonged mechanical ventilation, who would have died regardless of ICU treatment. Another explanation exists. Literature shows that prognostication for an individual patient remains difficult (32) and suggests the existence of self-fulfilling prophecy (SFP) in medical decision making, especially in EoL decisions (36). As comfort care inevitable leads to death, we might deprive patients with a malignancy the possibility of prolonged survival if we misjudge the prognosis of an individual patient. To prevent such a misjudgement, EoL decisions should be made in a multidisciplinary meeting.
Within the study population, no statistically significant difference in short-term mortality and long-term mortality was seen between patients with an active malignancy and patients with complete remission. However, a clinically relevant difference in 1-year mortality (67.2% vs 58.2%) and 2-year mortality (72% vs 59.5%) was seen between these groups. This finding suggests that for short-term mortality, other factors such as comorbidity and severity of illness should be considered as important factor for outcome, while the status of the malignancy plays an increasingly important role in long-term mortality. Patients with complete remission showed higher long-term mortality rates when compared to the patients without a malignancy. This finding may suggest an influence of previous cancer treatment (and therefore having a malignancy in CR) on long-term mortality. To our knowledge, the mortality of patients with an active malignancy compared to CR and the general population has not been directly described in the current literature.
Despite the higher mortality, we think it is important to note that the majority of the survivors had a good performance status 2 years after ICU admission, both in patients with an active malignancy as in patients with complete remission. Seventy-five percent of the patients with a known ECOG performance status scored 0 or 1. Our findings are consistent with Zafra and co-workers, in their study 79% of the survivors at 1 year after ICU admission showed an ECOG performance status of 0–2 (37).
The finding that performance status (measured by the ECOG performance status) was independently associated with short-term mortality and long-term mortality (33, 34, 38–40) is in line with other literature. Similar to our study, severity of illness (measured by the SOFA score) has been described in literature as predictor for short-term mortality in patients with a malignancy (30, 31, 41) and long-term mortality (38, 39, 42). Studies which describe SOFA score and performance status as long-term predictor have maximal 1 year of follow up after ICU admission. Our study shows that SOFA score and performance status are independently associated with 2 year mortality as well. To a lesser degree, age was a factor associated with mortality in our study. After an ICU admission, aging is associated with an increased risk of mortality in the 3 years after hospital discharge (43).
As SOFA score and ECOG performance status before ICU admission were independent predictors for short-term mortality and long-term mortality, the decision to deny a patient with a malignancy or a malignancy in their medical history an ICU admission should not solely be based on the presence of a malignancy. Instead, physicians should take the severity of illness and performance status into account before referring or admitting a patient to the ICU. In addition, ICU admission should also depend on the prognostic expectations of the patient. However, prognostication at individual patient level by clinicians remains difficult (1, 32). It is especially difficult in patients with a malignancy, due to the many factors related to the underlying malignancy (e.g. stage, type, hormone receptor status), and the estimation whether the patient will be able to receive future anti-cancer treatment after ICU admission (1, 32). Moreover, poor communication regarding outcome and expectations towards other health care providers or the patient and family has been described, either due to insufficient knowledge concerning prognostication or communication, or due to difficulty with sharing a poor prognosis (32, 44, 45). To improve prognostication and communication, good collaboration with open communication in multidisciplinary meetings and joint education regarding expectations and outcomes is essential (32).
Limitations and strengths
First, the most important limitation is the heterogeneity of the study population. However, by using a binary logistic regression analysis, the heterogeneity of the type of tumour (solid vs hematological) and the status of the malignancy (active vs CR) was minimalized. Literature shows clearly late negative effects of cancer therapies, even decades after completion of the cancer treatment (12–16). We therefore did not exclude patients with a malignancy in their distant past, which caused a wide variation of duration of CR.
Second, selection bias might have influenced our outcome, as our ICU physicians already made an admission decision before ICU admission. Nevertheless, our study population accounted for 20% of the unplanned ICU admissions, which is comparable to other literature. Therefore, the influence of selection bias should be limited.
Third, performance status is not similar to quality of life. However, since literature regarding long-term performance status after ICU admission in patients with a malignancy is very limited, our message of a good long-term performance status is important.
Fourth, data were collected from a single institution, which can restrict generalizability. However our institute is the biggest university clinic in the Netherlands, covering oncologic patient care for a population up to 3 million people.
Last, this was a retrospective study, and all the limitations of a retrospective review could be inherent in our study.