Outcomes for Critically Ill Cancer Patients in the ICU: Current Trends and Prediction. Int Anesthesiol Clin. 2016;54:e62-e75. [PMID: 27623129 DOI: 10.1097/aia.0000000000000121]

Short-term and long-term outcomes of critically ill patients with solid malignancy: a retrospective cohort study

BACKGROUND/AIMS

With the global increase in patients with solid malignancies, it is helpful to understand the outcomes of intensive care unit (ICU) admission for these patients. This study evaluated the risk factors for ICU mortality and the shortand long-term outcomes in patients with solid malignancies who had unplanned ICU admission.

METHODS

This retrospective cohort study included patients with solid malignancies treated at the medical ICU of a single tertiary center in South Korea between 2016 and 2022.

RESULTS

Among the 955 patients, the ICU mortality rate was 23.5%. Lung cancer was the most common cancer type (34.2%) and was significantly associated with increased ICU mortality (odd ratio [OR] 1.58, p = 0.030). Higher Sequential Organ Failure Assessment scores at ICU admission (OR 1.11, p < 0.001), the need for mechanical ventilation (OR 6.74, p < 0.001), or renal replacement therapy during the ICU stay (OR 2.49, p < 0.001) were significantly associated with higher ICU mortality. The 1-year survival rate after ICU admission was 29.3%, with a median survival of 37 days for patients requiring mechanical deviaventilation, and 23 days for patients requiring renal replacement therapy.

CONCLUSION

This study showed that critically ill patients with solid malignancies had poor 1-year survival despite relatively low ICU mortality. These findings highlight the need for careful consideration of ICU admission in patients with solid malignancy, and decision-making should be based on an understanding of the expected short- and long-term prognosis of ICU admission after an informed discussion among patients, families, and physicians.

FRailty in Australian patients admitted to Intensive care unit after eLective CANCER-related SURGery: a retrospective multicentre cohort study (FRAIL-CANCER-SURG study)

BACKGROUND

The association between frailty and short-term and long-term outcomes in patients receiving elective surgery for cancer remains unclear, particularly in those admitted to the ICU.

METHODS

In this multicentre retrospective cohort study, we included adults ≥16 yr old admitted to 158 ICUs in Australia from January 1, 2018 to March 31, 2022 after elective surgery for cancer. We investigated the association between frailty and survival time up to 4 yr (primary outcome), adjusting for a prespecified set of covariates. We analysed how this association changed in specific subgroups (age categories [<65, 65-80, ≥80 yr], and those who survived hospitalisation), and over time by splitting the survival information at monthly intervals.

RESULTS

We included 35,848 patients (median follow-up: 18.1 months [inter-quartile range: 8.3-31.1 months], 19,979 [56.1%] male, median age 69.0 yr [inter-quartile range: 58.8-76.0 yr]). Some 3502 (9.8%) patients were frail (defined as clinical frailty scale ≥5). Frailty was associated with lower survival (hazard ratio: 1.72, 95% confidence interval [CI]: 1.59-1.86 compared with clinical frailty scale ≤4); this was concordant across several sensitivity analyses. Frailty was most strongly associated with mortality early on in follow-up, up to 10 months (hazard ratio: 1.39, 95% CI: 1.03-1.86), but this association plateaued, and its predictive capacity subsequently diminished with time up until 4 yr (1.96, 95% CI: 0.73-5.28). Frailty was associated with similar effects when stratified based on age, and in those who survived hospitalisation.

CONCLUSIONS

Frailty was associated with poorer outcomes after an ICU admission after elective surgery for cancer, particularly in the short term. However, its predictive capacity with time diminished, suggesting a potential need for longitudinal reassessment to ensure appropriate prognostication in this population.

Clinical significance of serum lactate and lactate dehydrogenase levels for disease severity and clinical outcomes in patients with colorectal cancer admitted to the intensive care unit

Objective

Serum lactate (LA) and lactate dehydrogenase (LDH) levels have a major impact on the clinical treatment of malignant tumors and critically ill patients. Nevertheless, the assessment of disease severity in oncology patients admitted to the intensive care unit (ICU) remains incomplete when considering the serum LA and LDH levels. This study aimed to investigate the significance of serum LDH and LA levels in assessing disease severity and predicting clinical outcomes in patients with colorectal cancer (CRC) admitted to the ICU.

Methods

This retrospective study included patients with CRC who were admitted to the ICU between January 2017 and December 2022. The patients were divided into three groups based on the tumor treatment methods they had received within 3 months before ICU admission: post-chemotherapy group, post-surgery group, and palliative treatment group. The association between serum LA and LDH levels and disease severity and clinical outcomes was analyzed.

Results

Of 137 patients with CRC admitted to the ICU were finally studied. Patients in the post-chemotherapy group exhibited higher serum LA and LDH levels compared to those in the other two groups. Additionally, they had higher Acute Physiology and Chronic Health Evaluation (APACHE) II scores, longer ICU length of stay, and a higher 30-day mortality. We found a significant positive correlation between serum LA levels and APACHE II scores as well as ICU length of stay and 30-day mortality. In contrast, we only observed a significant positive correlation between serum LDH levels and disease severity in the post-chemotherapy group, whereas no significant correlation between LDH levels and 30-day mortality in any of the three groups.

Conclusion

Our study concludes that elevated serum LA levels, rather than LDH levels, are more effective in assessing disease severity and could be used as predictors for clinical outcomes in patients with CRC admitted to the ICU.

Dynamic Prediction of Patient Outcomes in the Intensive Care Unit: A Scoping Review of the State-of-the-Art

INTRODUCTION

Intensive care units (ICUs) are high-pressure, complex, technology-intensive medical environments where patient physiological data are generated continuously. Due to the complexity of interpreting multiple signals at speed, there are substantial opportunities and significant potential benefits in providing ICU staff with additional decision support and predictive modeling tools that can support and aid decision-making in real-time.This scoping review aims to synthesize the state-of-the-art dynamic prediction models of patient outcomes developed for use in the ICU. We define "dynamic" models as those where predictions are regularly computed and updated over time in response to updated physiological signals.

METHODS

Studies describing the development of predictive models for use in the ICU were searched, using PubMed. The studies were screened as per Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, and the data regarding predicted outcomes, methods used to develop the predictive models, preprocessing the data and dealing with missing values, and performance measures were extracted and analyzed.

RESULTS

A total of n = 36 studies were included for synthesis in our review. The included studies focused on the prediction of various outcomes, including mortality (n = 17), sepsis-related complications (n = 12), cardiovascular complications (n = 5), and other complications (respiratory, renal complications, and bleeding, n = 5). The most common classification methods include logistic regression, random forest, support vector machine, and neural networks.

CONCLUSION

The included studies demonstrated that there is a strong interest in developing dynamic prediction models for various ICU patient outcomes. Most models reported focus on mortality. As such, the development of further models focusing on a range of other serious and well-defined complications-such as acute kidney injury-would be beneficial. Furthermore, studies should improve the reporting of key aspects of model development challenges.

Outcome Prediction of Hematologic Malignancy in Critically Sick People

People with hematologic malignancies (HM) frequently postulate intensive care unit (ICU) hospitalization due to organ damage caused by the disease process or treatment-related consequences. This study is aimed at looking at mortality and sign factors in adult patients with hematologic malignancy (HM) who have been hospitalized in the ICU. Death was one quality indicator; researchers used a machine learning approach to find determinants of death. As per the study, there have been 206 patients hospitalized in the ICU (mean age: 51.3 ± 13.6 years; 60% male). The average length of stay was three days, with 14.1% requiring extended ICU commitment. ICU death was 45.6% at 30 days, 62.6% at sixty days, and 74.3% at twelve months, rising to 59.2% at thirty days, 62.6% at sixty days, and 74.3% at twelve months. Ventilation systems and vasodilating medication were linked to higher ICU death, but admission to the ICU surgically and experiencing malignancies are linked with lower death rates. Patients with HM who are hospitalized in the ICU have a high mortality rate (45.6%), which rises to 74.3% after a year. Serious illness, postsurgical hospitalization, and malignancy were revealed as determinants of patient outcomes in multivariate analyses.

Red blood cell distribution width-to-albumin ratio is associated with all-cause mortality in cancer patients

Background

Cancer causes a serious health burden on patients worldwide. Chronic low‐level inflammation plays a key role in tumorigenesis and prognosis. However, the role of the red blood cell distribution width (RDW)‐to‐albumin (RA) ratio in cancer mortality remains unclear.

Methods

In this retrospective cohort study, we collected clinical information from cancer patients from the Medical Information Mart for Intensive Care III (MIMIC‐III) version 1.4 database and then calculated RA by dividing RDW by albumin concentration. The primary outcome was 30 days mortality, while secondary outcomes were 90 days and 1 year mortality. Next, we adopted Cox regression models to calculate hazard ratios (HR) together with 95% confidence intervals (CI) for all‐cause mortalities associated with the RA ratio.

Results

For 30 days mortality, the HR (95% CI) for the high RA ratio (≥5.51) was 2.17 [95CI% (1.87–2.51); p = <0.0001], compared with the low RA ratio (<5.51). In Model 2, we adjusted sex and age and obtained HR (95% CI) of 2.17 [95CI% (1.87–2.52); p = <0.0001] for the high RA ratio (≥5.51) group, compared to that in the low RA ratio (<5.51). In Model 3, adjusting for age, sex, anion gap, hematocrit, white blood cell count, congestive heart failure, SOFA, liver disease, and renal failure resulted in HR (95% CI) of 1.74 [95CI% (1.48–2.04); p = <0.0001] for the high RA ratio (≥5.51) relative to the low RA ratio (<5.51). We also analyzed common diseases in cancer patients but found no significant association.

Conclusion

To the best of our knowledge, this is the first study demonstrating that increased RA ratio is independently associated with increased all‐cause mortality in cancer patients.

Triage and Prognostication of Cancer Patients Admitted to the Intensive Care Unit

Cancer remains a leading cause of morbidity and mortality. Advances in cancer screening, early detection, targeted therapies, and supportive care have led to improvements in outcomes and quality of life. The rapid increase in novel cancer therapies can cause life-threatening adverse events. The need for intensive care unit (ICU) care is projected to increase. Until 2 decades ago, cancer diagnosis often precluded ICU admission. Recently, substantial cancer survival has been achieved; therefore, ICU denial is not recommended. ICU resources are limited and expensive; hence, appropriate utilization is needed. This review focuses on triage and prognosis in critically ill cancer patients requiring ICU admission.

Critically ill patients with cancer: A clinical perspective

Cancer patients account for 15% of all admissions to intensive care unit (ICU) and 5% will experience a critical illness resulting in ICU admission. Mortality rates have decreased during the last decades because of new anticancer therapies and advanced organ support methods. Since early critical care and organ support is associated with improved survival, timely identification of the onset of clinical signs indicating critical illness is crucial to avoid delaying. This article focused on relevant and current information on epidemiology, diagnosis, and treatment of the main clinical disorders experienced by critically ill cancer patients.

Management of cancer patients during COVID-19 pandemic at developing countries

Cancer patient care requires a multi-disciplinary approach and multiple medical and ethical considerations. Clinical care during a pandemic health crisis requires prioritising the use of resources for patients with a greater chance of survival, especially in developing countries. The coronavirus disease 2019 crisis has generated new challenges given that cancer patients are normally not prioritised for admission in critical care units. Nevertheless, the development of new cancer drugs and novel adjuvant/neoadjuvant protocols has dramatically improved the prognosis of cancer patients, resulting in a more complex decision-making when prioritising intensive care in pandemic times. In this context, it is essential to establish an effective and transparent communication between the oncology team, critical care, and emergency units to make the best decisions, considering the principles of justice and charity. Concurrently, cancer treatment protocols must be adapted to prioritise according to oncologic response and prognosis. Communication technologies are powerful tools to optimise cancer care during pandemics, and we must adapt quickly to this new scenario of clinical care and teaching. In this new challenging pandemic scenario, multi-disciplinary work and effective communication between clinics, technology, science, and ethics is the key to optimising clinical care of cancer patients.

Costs and Outcomes of Patients Admitted to the Intensive Care Unit With Cancer

INTRODUCTION

Cancer is associated with significant health-care expenditure, but few studies have examined the cost of patients with cancer in the intensive care unit (ICU). We aimed to describe the costs and outcomes of patients admitted to the ICU with cancer.

METHODS

We conducted a retrospective cohort study of patients admitted between 2011 and 2016 to 2 tertiary-care ICUs. We included patients with a cancer-related most responsible diagnosis using International Classification of Disease, 10th Revision, Canada codes. We compared costs and outcomes of patients having cancer with noncancer controls matched for age, sex, and Elixhauser comorbidity score. We used logistic regression to determine predictors of mortality among patients with cancer.

RESULTS

There were 1022 patients with cancer during the study period. Mean age was 63.2 years and 577 (56.5%) were male. Inhospital mortality for all patients with cancer was 24.0%. Total cost per patient was higher for patients with cancer compared to noncancer patients (CAD$57 084 vs CAD$40 730; P < .001) but there were no differences in the cost per day (CAD$2868 vs CAD$2887; P = .76) or ICU cost (CAD$30 495 vs CAD$29 382; P = .42). Among patients with cancer, the cost per day was higher for nonsurvivors (CAD$3477 vs CAD$2677; P < .001). Liver disease (odds ratio [OR]: 2.96; 95% confidence interval [CI]: 1.22-7.81), mechanical ventilation (OR: 1.73; 95% CI: 1.25-2.39), hematologic malignancy (OR: 3.88; 95% CI: 2.31-6.54), and unknown primary site (OR: 2.13; 95% CI: 1.36-3.35) were independently associated with mortality in patients with cancer.

CONCLUSION

Patients admitted to the ICU with cancer did not differ in cost per day, ICU cost, or mortality compared to matched noncancer controls. Among patients with cancer, nonsurvivors had significantly higher cost per day compared to survivors. Hematologic and unknown primaries, liver disease, and mechanical ventilation were independently associated with mortality in patients with cancer.

Characteristics and outcomes of patients with solid tumors receiving chemotherapy in the intensive care unit

PURPOSE

The objective of this study was to evaluate the short- and long-term outcomes of adult patients with solid tumors receiving chemotherapy in the intensive care unit (ICU).

METHODS

This was a retrospective single-center study comparing the outcomes of patients with solid tumors who received chemotherapy in the ICU with a matched cohort of ICU patients (by age, sex, and tumor type) who did not receive chemotherapy. Conditional logistic regression and shared frailty Cox regression were used to assess short-term (ICU and hospital) mortality and death by 12-month post-hospital discharge, respectively.

RESULTS

Seventy-three patients with solid tumors who received chemotherapy in the ICU were successfully matched. The most common solid tumors included thoracic (30%), genitourinary (26%), and breast (16%). The ICU, hospital, and 12-month (post discharge)  mortality rates of patients who recieved chomtherapy in the ICU were 23%, 36%, and 43%, respectively. When compared to the matched cohort of patients who did not receive chemotherapy, patients who received chemotherapy had a significantly longer length of stay in the ICU (median 7 vs. 4 days, p < 0.001) and hospital (median 15 vs. 11 days, p = 0.011) but similar short-term ICU and hospital mortality rates (23% vs. 18% and 36% vs. 38%, respectively). Patients who received chemotherapy in the ICU were at a lower risk of death by 12 months (HR 0.31, p < 0.001) compared to the matched cohort on multivariable analysis.

CONCLUSIONS

Patients with solid tumors who received chemotherapy had increased ICU and hospital length of stay compared to patients who did not. Although short-term mortality did not differ, patients who received chemotherapy in the ICU had improved long-term survival. Our data can inform critical care triage decisions to include patients who are to receive chemotherapy in the ICU.

In-hospital and day-120 survival of critically ill solid cancer patients after discharge of the intensive care units: results of a retrospective multicenter study-A Groupe de recherche respiratoire en réanimation en Onco-Hématologie (Grrr-OH) study

Objectives

To assess outcomes at hospital discharge and day-120 after intensive care unit (ICU) discharge among patients with solid cancer admitted to ICU and to identify characteristics associated with in-hospital and day-120 after ICU discharge mortalities.

Design

International, multicenter, retrospective study.

Setting

Five ICUs in France and Brazil, two located in cancer centers, two in university affiliated and one in general hospitals.

Patients

Consecutive patients aged > 18 years, with underlying solid cancers (known before admission to the ICU or diagnosed during the stay in the ICU), admitted to the participating ICUs and discharged alive from the ICU from January 2006 to December 2011 were included in this study. Patients admitted after scheduled surgery or to secure procedure were excluded. Variables of interest were in-hospital and day-120 post-ICU mortality among patients discharged alive from the ICU.

Interventions

None.

Measurements and results

A total of 1053 patients aged 63 years (54–71) (median [IQR]) were included. Most of the patients were of the male gender (66.8%). The in-ICU, in-hospital, and four-month post-ICU discharge mortalities were, respectively, 41.3, 60.7, and 65.8%. Among patients discharged alive from the ICU, in multivariate analysis, factors associated with four months post-ICU discharge mortality were type of cancer (OR from 0.25 to 0.52 when compared to lung cancers), systemic extension of the disease (OR 2.54; 95% CI 1.87–3.45), need for invasive mechanical ventilation (OR 2.54; 95% CI 1.80–3.59), for vasopressors (OR 2.35; 95% CI 1.66–3.29), or renal replacement therapy (OR 1.54; 95% CI 0.99–2.38). A predictive score, “Oncoscore,” was built performing fairly in predicting 4 months post-ICU discharge outcome (AUC 0.74; 95% CI 0.71–0.77).

Conclusion

Despite the high day-120 mortality following the ICU discharge, our study reports a meaningful medium-term survival rate after the ICU discharge of solid cancer patients. Of utmost importance, the “Oncoscore” must be validated in prospective studies and cannot be used, in its form without external validation, for individual decision making. Prospective studies to answer questions not provided by this study are needed, including only patients with solid cancers admitted in the ICU for medical reasons or after emergency surgery.

Electronic supplementary material

The online version of this article (10.1186/s13613-018-0386-6) contains supplementary material, which is available to authorized users.