
==== Front
Ann Intensive Care
Ann Intensive Care
Annals of Intensive Care
2110-5820
Springer International Publishing Cham

1366
10.1186/s13613-024-01366-3
Research
Factors associated with cancer treatment resumption after ICU stay in patients with solid tumors
http://orcid.org/0000-0003-1596-493X
Benguerfi Soraya soraya.benguerfi@gmail.com

12
Messéant Ondine 3
Painvin Benoit 1
Camus Christophe 1
Maamar Adel 1
Gacouin Arnaud 1
Ricordel Charles 45
Reignier Jean 26
Canet Emmanuel 6
Edeline Julien 7
Tadié Jean-Marc 189
1 grid.410368.8 0000 0001 2191 9284 CHU Rennes, Service de Maladies Infectieuses et Réanimation Médicale, Hôpital Pontchaillou, Université de Rennes 1, 2, rue Henri Le Guilloux, Rennes cedex 9, 35033 France
2 https://ror.org/03gnr7b55 grid.4817.a 0000 0001 2189 0784 Laboratory “Movement, Interactions, Performance” (EA 4334), Faculty of Sport Sciences, University of Nantes, 25 Bis Boulevard Guy Mollet, BP 72206, Nantes Cedex 3, 44322 France
3 grid.411154.4 0000 0001 2175 0984 Service d’Hématologie Clinique, Hôpital Pontchaillou, CHU Rennes, Université de Rennes 1, 2, rue Henri Le Guilloux, Rennes cedex 9, 35033 France
4 https://ror.org/05qec5a53 grid.411154.4 0000 0001 2175 0984 CHU Rennes, Service de Pneumologie, 2 Rue Henri Le Guilloux, Rennes, 35033 France
5 grid.410368.8 0000 0001 2191 9284 INSERM, OSS (Oncogenesis Stress Signaling), UMR_S 1242, CLCC Eugene Marquis, Univ Rennes 1, Rennes, 35000 France
6 https://ror.org/03gnr7b55 grid.4817.a 0000 0001 2189 0784 CHU Nantes, Service de Médecine Intensive Réanimation, Nantes Université, 1 Place Alexis Ricordeau, Nantes Cedex 01, 44093 France
7 https://ror.org/015m7wh34 grid.410368.8 0000 0001 2191 9284 CLCC Eugène Marquis, Service d’Oncologie Médicale, Université de Rennes 1, COSS (Chemistry Oncogenesis Stress Signaling), UMR_S 1242, Rennes, France
8 grid.11619.3e 0000 0001 2152 2279 INSERM, Microenvironment, Cell Differentiation, Immunology, and Cancer-UMR_S1236, Établissement française du sang Bretagne, Université de Rennes 2, Rennes, F-35000 France
9 CIC 1414, Rennes, France
31 8 2024
31 8 2024
2024
14 13525 3 2024
9 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Background

Post-intensive care syndrome could be responsible for inability to receive proper cancer treatment after ICU stay in patients with solid tumors (ST). Our purpose was to determine the factors associated with cancer treatment resumption and the impact of cancer treatment on the outcome of patients with ST after ICU stay.

Methods

We conducted a retrospective study including all patients with ST admitted to the ICU between 2014 and 2019 in a French University-affiliated Hospital.

Results

A total of 219 patients were included. Median SAPS II at ICU admission was 44.0 [IQR 32.8, 66.3]. Among the 136 patients who survived the ICU stay, 81 (59.6%) received cancer treatment after ICU discharge. There was an important increase in patients with poor performance status (PS) of 3 or 4 after ICU stay (16.2% at admission vs. 44.5% of patients who survived), with significant PS decline following the ICU stay (median difference − 1.5, 95% confidence interval [-1.5-1.0], p < 0.001). The difference between the PS after and before ICU stay (delta PS) was independently associated with inability to receive cancer treatment (Odds ratio OR 0.34, 95%CI 0.18–0.56, p value < 0.001) and with 1-year mortality in patients who survived at ICU discharge (Hazard ratio HR 1.76, 95%CI 1.34–2.31, p value < 0.001). PS before ICU stay (OR 3.73, 95%IC 2.01–7.82, p value < 0.001) and length of stay (OR 1.23, 95%CI 1.06–1.49, p value 0.018) were independently associated with poor PS after ICU stay. Survival rates at ICU discharge, at 1 and 3 years were 62.3% (n = 136), 27.3% (n = 59) and 17.1% (n = 37), respectively. The median survival for patients who resumed cancer treatment after ICU stay was 771 days (95%CI 376–1058), compared to 29 days (95%CI 15–49) for those who did not resume treatment (p < 0.001).

Conclusion

Delta PS, before and after ICU stay, stands out as a critical determinant of cancer treatment resumption and survival after ICU stay. Multidisciplinary intervention to improve the general condition of these patients, in ICU and after ICU stay, may improve access to cancer treatment and long-term survival.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-024-01366-3.

Keywords

Neoplasms
Intensive care unit
Cancer treatment
Outcome
Solid tumors
issue-copyright-statement© La Société de Réanimation de Langue Francaise = The French Society of Intensive Care (SRLF) 2024
==== Body
pmcBackground

Although advances in oncology over the past few decades have led to a better prognosis in patients, cancer remains a public health problem and a leading cause of death worldwide [1].

Patients with cancer are exposed to infections, symptoms of cancer progression or drugs’ adverse effects, responsible for intensive care unit (ICU) admission [2, 3]. It is estimated that approximately 5% of patients with cancer may develop critical illness leading to ICU admission within two years of cancer diagnosis, affecting the patient’s outcome [4–6].

Among patients with cancer admitted to the ICU, several factors have been identified as associated with one-year mortality such as metastatic cancer, newly diagnosed cancer at ICU admission, cancer in progression under treatment, poor performance status (PS) and inability to receive oncologic treatment after ICU discharge [3, 7].

Post-intensive care syndrome, implying new or worsened impairments in physical, cognitive, and mental health, could be responsible for inability to receive full cancer treatment after ICU stay in patients with cancer [8]. This may be consequence of altered performance status and persistent organ dysfunction. Thus, a common fear among intensivists and oncologists is that ICU stay, especially when multiple organ support is required, will prevent further treatment of the cancer. However, no study has assessed the risk factors associated with the inability to receive cancer treatment after ICU stay in patients. Accordingly, we conducted a retrospective study to investigate the oncologic outcome of patients with solid tumors after ICU stay. The primary objective was to determine the factors associated with the resumption of cancer treatment after ICU stay in patients with cancer. The secondary objective was to determine the impact of cancer treatment on the long-term outcome of patients with cancer after ICU stay.

Methods

We conducted a retrospective single-centre study in a 30-bed general medical ICU located in a French University-affiliated Hospital. We included all patients with solid tumors admitted to the ICU between 2014 and 2019. Patients in complete remission from cancer were not included. Patients with treatment-limitation decision at ICU admission were excluded. Regarding patients with several ICU admissions, only the first ICU stay was considered. This work was approved by our institutional ethics committee (number 20.02).

Patient data were obtained retrospectively from electronic medical files. At ICU admission, age, Eastern Cooperative Oncology Group performance status (ECOG PS) [9], medical history, Simplified Acute Physiological Score II (SAPS II) [10], shock and infection were collected. Septic shock was defined according to the Sepsis-3 definition [11]. The cancer history was summarized by the following data: date of diagnosis, diagnosis in ICU, type of cancer, metastatic disease, cancer treatments received (chemotherapy, surgery, radiotherapy, immunotherapy, targeted therapy and/or hormotherapy), number of lines received, ongoing cancer treatment and its type. Cancer treatment was considered ongoing if it had been administered within the 2 months preceding ICU admission. The ICU stay was summarized by the following data: length of stay, reason for admission, maximum number of organ failures [12, 13] (as defined by the SOFA score [14] excluding thrombocytopenia which could be induced by treatment), maximum number of organ replacements, invasive or non-invasive mechanical ventilation, vasopressor support, renal-replacement therapy, extracorporeal membrane oxygenation, acute respiratory distress syndrome, cancer treatment during ICU stay and its type. After the ICU stay, we collected the following data: PS after ICU stay, cancer treatment administration (any systemic or local cancer treatment introduced after the ICU stay) and its type (chemotherapy, surgery, radiotherapy, immunotherapy, targeted therapy and/or hormotherapy), treatment adjustment (protocol chosen due to expected lower toxicity, dose reduction, early discontinuation of the treatment), tumor response to treatment (defined as stable disease, partial response, or complete response at the time of oncology assessment after cancer treatment introduction), date of first progression, outcome, cause of death, cancer status at death. An imaging assessment was systematically performed before resuming cancer treatment. Additionally, imaging assessments of treatment response were conducted every three months from the start of treatment.

Poor PS was defined as ECOG PS of 3 (capable of only limited selfcare; confined to bed or chair more than 50% of waking hours) or 4 (completely disabled; cannot carry on any selfcare; totally confined to bed or chair) [9]. The delta PS was defined as the difference between the PS after ICU stay and the PS before ICU stay. PS before ICU stay was obtained from the most recent report by the referring oncologist, completed within three months before admission. PS after ICU stay was collected within one week of ICU discharge.

Statistical analyses

Descriptive statistics were used to describe the study population. Patients who received cancer treatment after ICU stay and those who did not receive treatment were compared using Chi-square or Fisher Exact test, as appropriate, for categorical variables, or by Student t-test or Wilcoxon-Mann Whitney test, as appropriate, for continuous variables. A paired samples Wilcoxon test was employed to describe the evolution of PS before and after ICU stay in patients who survived at ICU discharge. Variables associated with cancer treatment resumption after ICU stay in univariable analysis with p < 0.1 were then entered into a multivariable logistic regression model after testing for collinearity. The length of invasive mechanical ventilation was excluded, while the length of stay was retained. An alluvial diagram was created to illustrate the resumption of cancer treatment based on the evolution of PS. Survival analysis was performed. Overall survival was defined as the duration from the date of ICU admission to death. Variables associated with survival in univariable analysis with p < 0.1 were entered into a Cox proportional hazards model after testing for collinearity and confirming the proportional hazards assumption. The cancer treatment resumption was excluded from the multivariable analysis model to minimize potential confounding biases. Survival rate according to cancer treatment resumption after ICU stay was described by using the Kaplan–Meier method. Variables associated with poor PS after ICU stay in univariable analysis with p < 0.1 were then entered into a multivariable logistic regression model after testing for collinearity. The length of invasive mechanical ventilation was excluded from the multivariable analysis model to minimize the effect of collinearity. The first-degree error alpha was fixed to 0.05 bilaterally. Statistical analysis was performed using ‘R’ statistical software.

Results

Overall population characteristics

Between 2014 and 2019, 219 patients with solid tumors were admitted to the ICU. Main characteristics of the study population are represented in the Table 1. Of note, 32 (16.2%) patients had a poor ECOG PS at admission (3 or 4). Tumors were mostly non-small cell lung (n = 51 [23.6%]), colorectal (n = 23 [10.6%]), breast (n = 17 [7.9%]), head and neck (n = 15 [6.9%]), esophageal (n = 13 [6.0%]) and prostate (n = 12 [5.6%]) cancers. Cancer treatment was ongoing in 81 (37.2%) of patients upon admission. Among the admitted patients, 68 (32.2%) were diagnosed with cancer during their ICU stay, while 48 (22.0%) had a confirmed cancer diagnosis but had not yet initiated first-line treatment. Furthermore, 21 patients had not undergone treatment in the 2 months preceding ICU admission due to a therapeutic pause. Main causes for ICU admission were acute respiratory failure (n = 75 [34.4%]), septic shock (n = 40 [18.3%]), cardiac arrest (n = 15 [6.9%]), status epilepticus (n = 13 [6.0%]), acute kidney injury (n = 12 [5.5%]), coma (n = 11 [5.0%]) and hemoptysis (n = 11 [5.0%]). Forty-eight (44.5%) patients had a poor ECOG PS after ICU stay. The performance status demonstrated statistically significant decline following the ICU stay (median difference − 1.5, 95% confidence interval CI [-1.5-1.0], p < 0.001).

Table 1 Characteristics of overall population

Characteristics	Overall population
(n = 219)	
Male sex, n (%)	149 (68.0)	
Age at ICU admission, median [IQR]	63 [54, 69]	
Poor performance status (3–4) before ICU stay, n (%)

Missing data = 22

	32 (16.2)	
Details of performance status, n (%)		
0	35 (17.8)	
1	100 (50.8)	
2	30 (15.2)	
3	30 (15.2)	
4	2 (1.0)	
Sites of cancer, n (%)

Missing data = 3

		
Non-small cell lung cancer	51 (23.6)	
Colorectal	23 (10.6)	
Breast	17 (7.9)	
Head and neck	15 (6.9)	
Esophageal	13 (6.0)	
Prostate	12 (5.6)	
Carcinoma of unknown primary	10 (4.6)	
Small cell lung cancer	8 (3.7)	
Kidney	7 (3.2)	
Bladder	7 (3.2)	
Ovarian	7 (3.2)	
Glioblastoma	7 (3.2)	
Testis	6 (2.8)	
Melanoma	5 (2.3)	
Others	28 (13.1)	
Time from cancer diagnosis to ICU admission (months), median [IQR]	4 [1, 20]	
Metastatic disease, n (%)

Missing data = 5

	141 (65.9)	
Treatment received before ICU, n (%)		
Radiotherapy	63 (28.8)	
Chemotherapy	91 (41.6)	
Immune checkpoint inhibitors	7 (3.2)	
Targeted therapy	19 (8.7)	
Hormonotherapy	18 (8.2)	
Number of treatment lines before ICU, median [IQR]

Missing data = 1

	1 [0, 1]	
Details		
0	116 (53.2)	
1	70 (32.1)	
2	16 (7.3)	
3	11 (5.0)	
4	2 (0.9)	
5	1 (0.5)	
7	2 (0.9)	
Ongoing cancer treatment, n (%)

Missing data = 1

	81 (37.2)	
Type of treatment, n (%)

Missing data = 2

		
Chemotherapy	42 (53.8)	
Hormonotherapy	5 (6.4)	
Targeted therapy	7 (9.0)	
Immune checkpoint inhibitors	3 (3.8)	
Radiotherapy and chemotherapy	10 (12.8)	
Chemotherapy and targeted therapy	10 (12.8)	
Chemotherapy and hormonotherapy	1 (1.3)	
SAPS II, median [IQR]

Missing data = 3

	44.0 [32.8, 66.3]	
Cause for ICU admission, n (%)

Missing data = 1

		
Acute respiratory failure	75 (34.4)	
Septic shock	40 (18.3)	
Cardiac arrest	15 (6.9)	
Status epilepticus	13 (6.0)	
Acute kidney injury	12 (5.5)	
Coma	11 (5.0)	
Hemoptysis	11 (5.0)	
Sepsis	9 (4.1)	
Cardiogenic shock	6 (2.8)	
Others	26 (12.4)	
Diagnosis of cancer in ICU, n (%)	68 (31.1)	
Cancer treatment during ICU stay, n (%)

Missing data = 1

	13 (6.0)	
Type of treatment, n (%)		
Chemotherapy	6 (46.2)	
Targeted therapy	2 (15.4)	
Surgery	5 (38.5)	
Shock, n (%)	84 (38.4)	
Infection at ICU admission, n (%)	116 (53.0)	
Site of infection, n (%)

Missing data = 3

		
Respiratory	63 (56.3)	
Cutaneous	1 (0.9)	
Urinary	12 (10.7)	
Digestive	14 (12.5)	
Bloodstream infection	5 (4.5)	
Catheter-related bloodstream infection	6 (5.4)	
Fungemia	1 (0.9)	
Others	11 (9.9)	
Maximum number of organ failures, median [IQR]

Missing data = 2

	2 [1, 3]	
Maximum number of organ replacements, median [IQR]

Missing data = 3

	1 [0, 2]	
Invasive mechanical ventilation, n (%)

Missing data = 1

	131 (60.1)	
Non invasive ventilation, n (%)

Missing data = 1

	17 (7.8)	
High-flow nasal cannula therapy, n (%)

Missing data = 1

	9 (4.1)	
Vasopressor support, n (%)

Missing data = 1

	99 (45.4)	
Renal-replacement therapy, n (%)

Missing data = 3

	30 (13.9)	
V-A ECMO, n (%)

Missing data = 1

	1 (0.5)	
V-V ECMO, n (%)

Missing data = 1

	2 (0.9)	
Acute respiratory distress syndrome, n (%)

Missing data = 1

	15 (6.9)	
Length of invasive mechanical ventilation (days),

median [IQR]

Missing data = 1

	5.5 [2.0, 10.0]	
Length of stay (days), median [IQR]	5 [2, 9]	
Poor performance status (3–4) after ICU stay, n (%)

Missing data = 28

	48 (44.5)	
Details of performance status, n (%)		
0	3 (2.8)	
1	40 (37.0)	
2	17 (15.7)	
3	29 (26.9)	
4	19 (17.6)	
IQR: interquartile range. ICU: intensive care unit. SAPS II: Simplified Acute Physiological Score II. V-A ECMO: veno-arterial extracorporeal membrane oxygenation. V-V ECMO: veno-venous extracorporeal membrane oxygenation

Factors associated with cancer treatment resumption after ICU stay

Among the 136 patients who survived the ICU stay, 81 (59.6%) received cancer treatment after ICU discharge. The main treatments were chemotherapy (n = 32 [39.5%]), surgery (n = 11 [13.6%]), radiotherapy (n = 9 [11.1%]), hormonotherapy (n = 7 [8.6%]) or immune checkpoint inhibitors (n = 5 [6.2%]). A treatment adjustment was made for 19 (30.2%) patients. Tumor response to treatment (defined as stable disease, partial response, or complete response at the time of oncology assessment after cancer treatment introduction) was observed in 57 (70.4%) patients, with the best overall response being complete response in 19 (33.3%) patients, partial response in 25 (43.9%), and stable disease in 10 (17.5%). Following the initiation of treatment after the ICU stay, 16 patients (21.9%) experienced disease progression without any tumor response.

Characteristics of the population according to cancer treatment resumption and univariable analysis are shown in the Table 2. A logistic regression model was used to explore the association of infection, length of stay, maximum number of organ failures, maximum number of organ replacements and delta PS, with cancer treatment resumption after ICU stay. At multivariable analysis, delta PS (Odds ratio OR 0.34, 95%CI 0.18–0.56, p value < 0.001) was independently associated with inability to receive cancer treatment (Table 3).

Table 2 Characteristics of population according to cancer treatment resumption and univariable analysis

Characteristics	No treatment after ICU
(n = 49)	Treatment after ICU
(n = 81)	p	
Male sex, n (%)	33 (67.3)	59 (72.8)	0.553	
Age at ICU admission, median [IQR]	64 [56, 72]	63 [53, 68]	0.231	
Poor performance status (3–4) before ICU stay, n (%)

Missing data = 22

	9 (20)	5 (6.6)	0.040	
Details of performance status, n (%)				
0	5 (11.1)	21 (27.6)		
1	23 (51.1)	39 (51.3)		
2	8 (17.8)	11 (14.5)		
3	8 (17.8)	5 (6.6)		
4	1 (2.2)	0 (0.0)		
Sites of cancer, n (%)

Missing data = 3

			0.181	
Non-small cell lung cancer	11 (22.9)	18 (22.2)		
Colorectal	7 (14.6)	7 (8.6)		
Breast	3 (6.2)	7 (8.6)		
Head and neck	0 (0.0)	9 (11.1)		
Esophageal	7 (14.6)	2 (2.5)		
Prostate	2 (4.2)	7 (8.6)		
Carcinoma of unknown primary	3 (6.2)	1 (1.2)		
Small cell lung cancer	1 (2.1)	2 (2.5)		
Kidney	1 (2.1)	2 (2.5)		
Bladder	2 (4.2)	2 (2.5)		
Ovarian	1 (2.1)	2 (2.5)		
Glioblastoma	1 (2.1)	5 (6.2)		
Testis	1 (2.1)	2 (2.5)		
Melanoma	1 (2.1)	2 (2.5)		
Others	7 (14.7)	13 (16.0)		
Metastatic disease, n (%)

Missing data = 5

	30 (61.2)	45 (56.2)	0.713	
Treatment received before ICU, n (%)				
Radiotherapy	15 (30.6)	24 (29.6)	1.000	
Chemotherapy	23 (46.9)	30 (37.0)	0.276	
Immune checkpoint inhibitors	1 (2.0)	4 (4.9)	0.649	
Targeted therapy	7 (14.3)	7 (8.6)	0.385	
Hormonotherapy	3 (6.1)	7 (8.6)	0.742	
Number of treatment lines before ICU, median [IQR]

Missing data = 1

	0 [0, 1]	1 [0, 1]	0.683	
Ongoing cancer treatment, n (%)

Missing data = 1

	15 (31.2)	29 (35.8)	0.702	
Type of treatment, n (%)

Missing data = 1

			0.210	
Chemotherapy	5 (33.3)	13 (48.1)		
Hormonotherapy	0 (0.0)	2 (7.4)		
Targeted therapy	2 (13.3)	0 (0.0)		
Immune checkpoint inhibitors	0 (0.0)	3 (11.1)		
Radiotherapy and chemotherapy	4 (26.7)	4 (14.8)		
Chemotherapy and targeted therapy	4 (26.7)	4 (14.8)		
Chemotherapy and hormonotherapy	0 (0.0)	1 (3.7)		
SAPS II, median [IQR]

Missing data = 3

	41.0

[31.0, 56.0]

	37.0

[28.8, 47.0]

	0.129	
Cause for ICU admission, n (%)

Missing data = 1

			0.330	
Acute respiratory failure	20 (40.8)	21 (26.2)		
Septic shock	11 (22.4)	8 (10.0)		
Cardiac arrest	3 (6.1)	2 (2.5)		
Status epilepticus	3 (6.1)	9 (11.2)		
Acute kidney injury	2 (4.1)	7 (8.8)		
Coma	0 (0.0)	7 (8.8)		
Hemoptysis	2 (4.1)	5 (6.2)		
Infection without shock	3 (6.1)	6 (7.5)		
Cardiogenic shock	0 (0.0)	1 (1.2)		
Others	5 (10.1)	14 (17.3)		
Diagnosis of cancer in ICU, n (%)	15 (30.6)	21 (25.9)	0.686	
Cancer treatment during ICU stay, n (%)

Missing data = 1

	2 (4.1)	4 (5.0)	1.000	
Type of treatment, n (%)			1.000	
Chemotherapy	1 (50.0)	1 (25.0)		
Targeted therapy	0 (0.0)	0 (0.0)		
Surgery	1 (50.0)	3 (75.0)		
Shock, n (%)	14 (28.6)	21 (25.9)	0.839	
Infection, n (%)	31 (63.3)	37 (45.7)	0.070	
Site of infection, n (%)

Missing data = 3

			0.331	
Respiratory	17 (54.8)	17 (47.3)		
Cutaneous	1 (3.2)	0 (0.0)		
Urinary	5 (16.2)	7 (19.4)		
Digestive	2 (6.5)	3 (8.3)		
Bloodstream infection	1 (3.2)	1 (2.8)		
Catheter-related bloodstream infection	0 (0.0)	3 (8.4)		
Fungemia	1 (3.2)	0 (0.0)		
Others	4 (12.8)	5 (14)		
Maximum number of organ failures, median [IQR]

Missing data = 2

	2 [1, 3]	1 [1, 2]	0.005	
Maximum number of organ replacements, median [IQR]

Missing data = 3

	1 [1, 1]	1 [0, 1]	0.017	
Invasive mechanical ventilation, n (%)

Missing data = 1

	24 (49.0)	32 (40.0)	0.362	
Non invasive ventilation, n (%)

Missing data = 1

	7 (14.3)	4 (5.0)	0.102	
High-flow nasal cannula therapy, n (%)

Missing data = 1

	5 (10.2)	2 (2.5)	0.104	
Vasopressor support, n (%)

Missing data = 1

	18 (36.7)	19 (23.8)	0.160	
Renal-replacement therapy, n (%)

Missing data = 3

	6 (12.2)	4 (5.0)	0.178	
V-A ECMO, n (%)

Missing data = 1

	0 (0.0)	0 (0.0)	1.000	
V-V ECMO, n (%)

Missing data = 1

	0 (0.0)	1 (1.2)	1.000	
Acute respiratory distress syndrome, n (%)

Missing data = 1

	2 (4.1)	1 (1.2)	0.557	
Length of invasive mechanical ventilation (days),

median [IQR]

Missing data = 1

	9.0

[4.0, 11.0]

	3.0

[1.0, 7.0]

	0.004	
Length of stay (days), median [IQR]	6 [2, 11]	4 [2, 6]	0.041	
Poor performance status (3–4) after ICU stay, n (%)

Missing data = 28

	32 (82.1)	15 (22.4)	< 0.001	
Details of performance status, n (%)				
0	1 (2.6)	2 (3.0)		
1	2 (5.1)	37 (55.2)		
2	4 (10.3)	13 (19.4)		
3	15 (38.5)	14 (20.9)		
4	17 (43.6)	1 (1.5)		
IQR: interquartile range. ICU: intensive care unit. SAPS II: Simplified Acute Physiological Score II. V-A ECMO: veno-arterial extracorporeal membrane oxygenation. V-V ECMO: veno-venous extracorporeal membrane oxygenation

Table 3 Multivariable analysis of factors associated with treatment resumption

Variables	Multivariable analysis	
OR (95% CI)	p	
Infection	0.79 (0.26–2.37)	0.666	
Length of stay	0.99 (0.92–1.07)	0.863	
Maximum number of organ failures	0.90 (0.51–1.61)	0.728	
Maximum number of organ replacements	1.12 (0.44–2.91)	0.807	
Delta PS	0.34 (0.18–0.56)	< 0.001	
PS: performance status

Figure 1 was designed to illustrate the resumption of cancer treatment based on the evolution of PS.

Fig. 1 Alluvial diagram illustrating the resumption of cancer treatment based on the evolution of performance status

Outcome

Survival rates at ICU discharge, at 6 months, at 1, 2 and 3 years were 62.3% (n = 136), 35.1% (n = 76), 27.3% (n = 59), 21.8% (n = 47) and 17.1% (n = 37), respectively.

The main causes of death in ICU were infection (n = 32 [39.0%]), cancer-related (n = 28 [34.1%]), cardiac arrest (n = 9 [11.0%]), specific toxicity of the cancer treatment (n = 5 [6.1%]) and stroke (n = 3 [3.7%]). Four patients had treatment limitations during their ICU stay, which was followed by death in the ICU.

After a median follow up of 65 months [interquartile range 49–78] after ICU discharge, 102 (76.7%) patients died. Median overall survival of patients who survived the ICU stay was 9.0 months (95% confidence interval [5.0-12.6]). The majority of deaths after ICU stay were ultimately cancer-related (n = 76 [86.4%]), four patients (4.5%) died from infection. At the time of death, cancer remained predominantly active (n = 108 [85.7%]), with few patients in remission or cured (n = 18 [14.3%]).

A Cox regression model was used to explore the association of delta PS, metastatic disease and diagnosis of cancer in ICU with 1-year mortality in patients who survived at ICU discharge. At multivariable analysis, delta PS (HR 1.76, 95%CI 1.34–2.31, p value < 0.001) was independently associated with 1-year mortality in patients who survived at ICU discharge (Table 4).

Table 4 Multivariable analysis of factors associated with 1-year mortality in patients who survived at ICU discharge

Variables	Multivariable analysis	
HR (95% CI)	p	
Delta PS	1.76 (1.34–2.31)	< 0.001	
Metastatic disease	1.72 (0.95–3.11)	0.072	
Diagnosis of cancer in ICU	1.50 (0.82–2.73)	0.185	
PS: performance status. ICU: intensive care unit

Another Cox regression model was used to explore the association of delta PS, cardiovascular disease, cirrhosis, shock, diagnosis of cancer in ICU and maximum number of organ replacements, with 3-year mortality in patients who survived at ICU discharge. At multivariable analysis, delta PS (HR 1.86, 95%CI 1.44–2.39, p value < 0.001), cardiovascular disease (HR 0.34, 95%CI 0.17–0.68, p value 0.002) and cirrhosis (HR 2.91, 95%CI 1.13–7.49, p value 0.027) was independently associated with 3-year mortality in patients who survived at ICU discharge.

The survival rate according to cancer treatment resumption after ICU stay was described by using the Kaplan–Meier method (Fig. 2). The median survival for patients who resumed cancer treatment after ICU stay was 771 days (95%CI 376–1058), compared to 29 days (95%CI 15–49) for those who did not resume treatment (p < 0.001). Cancer treatment adjustment was not associated with 1-year mortality (p = 0.293) or 3-year mortality (p = 0.413) in univariate analysis. The patient’s course from ICU admission to treatment resumption was illustrated in a flow chart (supplementary figure S1).

Fig. 2 Overall survival curves according to cancer treatment resumption

Factors associated with poor PS after ICU

A logistic regression model was used to explore the association of PS before ICU stay, infection, length of stay, maximum number of organ failures and maximum number of organ replacements, with poor PS after ICU stay. At multivariable analysis, PS before ICU stay (OR 3.73, 95%IC 2.01–7.82, p value < 0.001) and length of stay (OR 1.23, 95%CI 1.06–1.49, p value 0.018) was independently associated with poor PS after ICU stay (Table 5).

Table 5 Multivariable analysis of factors associated with poor PS after ICU

Variables	Multivariable analysis	
OR (95% CI)	p	
PS before ICU stay	3.73 (2.01–7.82)	< 0.001	
Infection	2.29 (0.78–6.96)	0.134	
Length of stay	1.23 (1.06–1.49)	0.018	
Maximum number of organ failures	1.38 (0.73–2.70)	0.327	
Maximum number of organ replacements	0.70 (0.25–1.91)	0.487	
PS: performance status. ICU: intensive care unit

Discussion

In this retrospective study, we found that the change in PS before and after ICU stay (delta PS) was associated with inability to receive cancer treatment. To our knowledge, this is the first study assessing factors associated with cancer treatment resumption after ICU stay. In our study, 59.6% of the patients surviving the ICU stay were receiving cancer treatment after ICU stay. The median survival for patients who resumed cancer treatment after ICU stay was 771 days (95%CI 376–1058), compared to 29 days (95%CI 15–49) for those who did not resume treatment (p < 0.001). ICU stay has a tremendous impact on PS as we observed an important increase in patients with poor PS of 3 or 4 after ICU stay (16.2% at ICU admission vs. 44.5% of patients who survived), with statistically significant PS decline following the ICU stay. PS before ICU stay and length of stay was associated with poor PS after ICU stay. Importantly, the main cause of death after ICU stay was cancer related. Moreover, we found that delta PS was associated with 1-year mortality in patients who survived ICU discharge. Additionally, delta PS, along with cardiovascular disease and cirrhosis, was independently associated with 3-year mortality in these patients.

Delta PS was associated with inability to receive cancer treatment after ICU stay, and factors associated with poor PS after ICU stay included PS before ICU stay and the length of ICU stay. On one hand, these elements may inform ethical considerations. They suggest that a cancer patient with impaired PS before ICU admission may experience further deterioration during the ICU stay, potentially hindering the resumption of cancer treatment and affecting survival outcomes. These findings underscore the importance of carefully evaluating the potential benefits and risks of ICU admission for such patients. The impact of PS before ICU stay on cancer patients outcome has been widely demonstrated [15, 16]. However, more than PS at any given time, delta PS may have a greater impact on the resumption of cancer treatment and patient outcome. This change in PS, observable over the course of the ICU stay, could provide valuable insights during ICU trials [17]. On the other hand, preventive strategies to prevent PS decline during the ICU stay, or to improve it afterwards, might impact patient’s outcome. There was an important increase in patients with poor PS of 3 or 4 after ICU stay. PS is a major factor in oncology decision-making, as evidenced by the inclusion criteria for clinical trials that require good general condition [18]. As a result, 59.6% of patients received cancer treatment after ICU stay. García de Herreros et al. also demonstrated a significant impact of ICU stay on PS, with 40% of survivors experiencing permanent discontinuation of cancer treatment [19]. While active mobilization and rehabilitation in the ICU have shown potential benefits for improving mobility and muscle strength in general population, the results of this type of intervention remain mixed and require further exploration [20, 21]. Notably, active physiotherapy in the ICU for intubated patients with malignancy has been demonstrated to be feasible and safe [22]. However, an individualized eight-week home-based physical rehabilitation program did not increase the underlying rate of recovery after ICU stay, with both groups of critically ill survivors improving their physical function over the 26 weeks of follow-up [23]. To date, no trial has assessed the effectiveness of combined nutritional and physical rehabilitation initiated in the ICU and continued after ICU stay, either in the general population or specifically in cancer patients. Interestingly, Gheerbrant et al. showed the evolution of PS over time in survivors with 20.2% of patients with poor PS at admission versus 12.7% at 3 months and 8.2% at 6 months. At 3 months, 55% of patients received cancer treatment [15].

The median survival for patients who resumed cancer treatment after ICU stay was 771 days, compared to 29 days for those who did not resume treatment. The observed difference in survival seems likely to be due to the early mortality of patients who do not resume treatment, rather than the effect of resuming cancer treatment itself, as 50% of these patients die within the month following ICU discharge. In our study, cancer patients who resumed treatment after ICU stay had prolonged survival. Resuming cancer treatment in these patients may significantly improve survival by controlling the underlying disease. Their prognosis after ICU stay appears to be mainly related to the cancer evolution. Conversely, those who did not resume treatment had a median survival of less than one month, with approximately 80% in a compromised general condition, making the resumption of treatment unlikely in this population. Their prognosis appears to be more related to the acute event leading to ICU admission rather than the cancer itself. The study suggests that the long-term mortality of patients may also be linked to their comorbidities, potentially stemming from either the impediment to receiving optimal cancer treatment or complications directly arising from the comorbidity itself [24]. Noteworthy, patient survival in our study was lower compared to the literature [3, 7]. This could be attributed to the inclusion criteria that specifically targeted patients with cancer in place, who may present more severe conditions. At ICU discharge, the prognosis of these patients might be worse because of the cancer in place. Gheerbrant et al. showed that 29% of patients had no indication for cancer treatment at 3 months after ICU discharge in a study allowing the inclusion of patients with cancer in remission for less than 5 years [15]. This suggests that many patients might be cured.

Therefore, ICU stay alters general condition and probably limit but does not prevent cancer treatment resumption. This should not prevent the patient from being admitted in ICU. The evolution of PS from ICU admission to discharge stands out as a critical determinant of oncologic outcomes, especially regarding cancer treatment resumption and long-term survival. The patient’s overall condition, especially its trajectory throughout their ICU stay, could significantly inform ethical considerations regarding the care of these individuals. Implementing comprehensive specialized management, encompassing aspects such as nutrition, physical rehabilitation, psychological support, emerges as a crucial component for facilitating the resumption of cancer treatments and enhancing the survival of these patients after ICU stay [25, 26].

This study has several strengths. Noteworthy, the general characteristics of our study population were in line with the literature [3]. The predominant cancer types in our study population were consistent with cancers epidemiology in Europe, except for head and neck and esophageal cancers which are overrepresented [27]. The higher level of comorbidities in some patients with head and neck and esophageal cancers, or the more frequent occurrence of respiratory complications in these patients, may provide an explanation for these results [28–30]. Notably, this study is the first to assess factors associated with the resumption of cancer treatment after an ICU stay in patients with cancer. It adopts a pragmatic approach, aiming to assist physicians in decision-making when confronted with complex medical and ethical situations. Cured patients or patients in remission were not included in the study, which allowed to meet the main objective, to focus on the more complex situations and to avoid overestimating the survival of patients with cancer admitted to the ICU. Patients with treatment-limitation decisions at ICU admission were excluded from the study. Significant variability in ICU triage decisions for cancer patients has been documented [31]. Admission policies differ across centers, with some admitting few or no cancer patients with treatment limitations due to their prognosis impact. Excluding these patients aids in meeting the primary objective by avoiding confounding factors, as this specific group often has more compromised conditions and oncological treatment restrictions. This exclusion also enhances the generalizability of our results. However, the study also has several limitations. Firstly, it is a single-center study, which may limit the generalizability of our results. Secondly, while our patient selection criteria are designed to meet our objectives by minimizing known confounding factors, they consequently select for a population with high proportion of patients diagnosed either in ICU or recently diagnosed, and do not provide information on patients with treatment-limitation decision. Thirdly, the retrospective nature of the study introduces potential biases. Certain data are missing, such as disease status (controlled disease, relapse, or progression) at the time of ICU admission or whether ICU admission was due to specific cancer treatment toxicity, potentially introducing confounding bias. Lastly, patients were included from 2014 to 2019. Oncology is undergoing a major therapeutic revolution across time, which means that cancer treatments change rapidly over time but also that patient prognosis may change accordingly.

Conclusion

Delta PS, before and after ICU stay, was independently associated with inability to receive cancer treatment, and with long-term mortality in patients who survived at ICU discharge. There was an important increase in patients with poor PS of 3 or 4 after ICU stay. More than half of the patients surviving the ICU stay were receiving cancer treatment after ICU stay. The median survival for patients who resumed cancer treatment after ICU stay was 771 days, compared to 29 days for those who did not resume treatment. Outcome of patients with cancer after ICU stay may be determined by their general condition and their oncological outcome. These findings can provide valuable insights for ethical considerations both before ICU admission and throughout the patient’s stay. Special attention should be paid to these patients at ICU discharge for comprehensive evaluation. Multidisciplinary intervention to improve the general condition of these patients may improve access to cancer treatment and long-term survival.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Acknowledgements

Not applicable.

Author contributions

SB and JMT designed the study and wrote the manuscript. SB, OM, BP and CC collected the data. SB and AM performed the statistical analysis. AG, CR, JR, EC and JE revised the manuscript.

Funding

No financial support was received for the work reported in this manuscript.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This work was approved by our institutional ethics committee (number 20.02). All survivors received information letter about the study, giving them the choice to decline participation in the study.

Consent for publication

All authors reviewed and consent for publication.

Competing interests

The authors declare no conflict of interest in relation to this study.

Abbreviations

ICU Intensive care unit

ST Solid tumors

PS Performance status

OR Odds ratio

HR Hazard ratio

ECOG PS Eastern Cooperative Oncology Group performance status

SAPS II Simplified Acute Physiological Score II

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Siegel RL Miller KD Wagle NS Jemal A Cancer statistics, 2023 CA Cancer J Clin 2023 73 17 48 10.3322/caac.21763 36633525
Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73:17–48.36633525 10.3322/caac.21763
2. Shimabukuro-Vornhagen A Böll B Kochanek M Azoulay É von Bergwelt-Baildon MS Critical care of patients with cancer CA Cancer J Clin 2016 66 496 517 10.3322/caac.21351 27348695
Shimabukuro-Vornhagen A, Böll B, Kochanek M, Azoulay É, von Bergwelt-Baildon MS. Critical care of patients with cancer. CA Cancer J Clin. 2016;66:496–517.27348695 10.3322/caac.21351
3. Vigneron C Charpentier J Valade S Alexandre J Chelabi S Palmieri L-J Patterns of ICU admissions and outcomes in patients with solid malignancies over the revolution of cancer treatment Ann Intensive Care 2021 11 182 10.1186/s13613-021-00968-5 34951668
Vigneron C, Charpentier J, Valade S, Alexandre J, Chelabi S, Palmieri L-J, et al. Patterns of ICU admissions and outcomes in patients with solid malignancies over the revolution of cancer treatment. Ann Intensive Care. 2021;11:182.34951668 10.1186/s13613-021-00968-5
4. Puxty K McLoone P Quasim T Sloan B Kinsella J Morrison DS Risk of critical illness among patients with solid cancers: a Population-based observational study JAMA Oncol 2015 1 1078 85 10.1001/jamaoncol.2015.2855 26313462
Puxty K, McLoone P, Quasim T, Sloan B, Kinsella J, Morrison DS. Risk of critical illness among patients with solid cancers: a Population-based observational study. JAMA Oncol. 2015;1:1078–85.26313462 10.1001/jamaoncol.2015.2855
5. Darmon M Bourmaud A Georges Q Soares M Jeon K Oeyen S Changes in critically ill cancer patients’ short-term outcome over the last decades: results of systematic review with meta-analysis on individual data Intensive Care Med 2019 45 977 87 10.1007/s00134-019-05653-7 31143998
Darmon M, Bourmaud A, Georges Q, Soares M, Jeon K, Oeyen S, et al. Changes in critically ill cancer patients’ short-term outcome over the last decades: results of systematic review with meta-analysis on individual data. Intensive Care Med. 2019;45:977–87.31143998 10.1007/s00134-019-05653-7
6. Bos MMEM Verburg IWM Dumaij I Stouthard J Nortier JWR Richel D Intensive care admission of cancer patients: a comparative analysis Cancer Med 2015 4 966 76 10.1002/cam4.430 25891471
Bos MMEM, Verburg IWM, Dumaij I, Stouthard J, Nortier JWR, Richel D, et al. Intensive care admission of cancer patients: a comparative analysis. Cancer Med. 2015;4:966–76.25891471 10.1002/cam4.430
7. Borcoman E Dupont A Mariotte E Doucet L Joseph A Chermak A One-year survival in patients with solid tumours discharged alive from the intensive care unit after unplanned admission: a retrospective study J Crit Care 2020 57 36 41 10.1016/j.jcrc.2020.01.027 32032902
Borcoman E, Dupont A, Mariotte E, Doucet L, Joseph A, Chermak A, et al. One-year survival in patients with solid tumours discharged alive from the intensive care unit after unplanned admission: a retrospective study. J Crit Care. 2020;57:36–41.32032902 10.1016/j.jcrc.2020.01.027
8. Needham DM, Davidson J, Cohen H, Hopkins RO, Weinert C, Wunsch H et al. Improving long-term outcomes after discharge from intensive care unit: report from a stakeholders’ conference. Crit Care Med. 2012;40:502–9.
9. Oken MM Creech RH Tormey DC Horton J Davis TE McFadden ET Toxicity and response criteria of the Eastern Cooperative Oncology Group Am J Clin Oncol 1982 5 649 55 10.1097/00000421-198212000-00014 7165009
Oken MM, Creech RH, Tormey DC, Horton J, Davis TE, McFadden ET, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982;5:649–55.7165009 10.1097/00000421-198212000-00014
10. Le Gall JR Lemeshow S Saulnier F A new simplified Acute Physiology score (SAPS II) based on a European/North American multicenter study JAMA 1993 270 2957 63 10.1001/jama.1993.03510240069035 8254858
Le Gall JR, Lemeshow S, Saulnier F. A new simplified Acute Physiology score (SAPS II) based on a European/North American multicenter study. JAMA. 1993;270:2957–63.8254858 10.1001/jama.1993.03510240069035
11. Singer M Deutschman CS Seymour CW Shankar-Hari M Annane D Bauer M The Third International Consensus definitions for Sepsis and septic shock (Sepsis-3) JAMA 2016 315 801 10 10.1001/jama.2016.0287 26903338
Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus definitions for Sepsis and septic shock (Sepsis-3). JAMA. 2016;315:801–10.26903338 10.1001/jama.2016.0287
12. de Vries VA Müller MCA Arbous MS Biemond BJ Blijlevens NMA Kusadasi N Long-term outcome of patients with a hematologic malignancy and multiple organ failure admitted at the Intensive Care Crit Care Med 2019 47 e120 8 10.1097/CCM.0000000000003526 30335623
de Vries VA, Müller MCA, Arbous MS, Biemond BJ, Blijlevens NMA, Kusadasi N, et al. Long-term outcome of patients with a hematologic malignancy and multiple organ failure admitted at the Intensive Care. Crit Care Med. 2019;47:e120–8.30335623 10.1097/CCM.0000000000003526
13. Orvain C Beloncle F Hamel J-F Del Galy AS Thépot S Mercier M Allogeneic stem cell transplantation recipients requiring intensive care: time is of the essence Ann Hematol 2018 97 1601 9 10.1007/s00277-018-3320-y 29717367
Orvain C, Beloncle F, Hamel J-F, Del Galy AS, Thépot S, Mercier M, et al. Allogeneic stem cell transplantation recipients requiring intensive care: time is of the essence. Ann Hematol. 2018;97:1601–9.29717367 10.1007/s00277-018-3320-y
14. Vincent JL Moreno R Takala J Willatts S De Mendonça A Bruining H The SOFA (Sepsis-related Organ failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-related problems of the European Society of Intensive Care Medicine Intensive Care Med 1996 22 707 10 10.1007/BF01709751 8844239
Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis-related Organ failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-related problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22:707–10.8844239 10.1007/BF01709751
15. Gheerbrant H Timsit J-F Terzi N Ruckly S Laramas M Levra MG Factors associated with survival of patients with solid Cancer alive after intensive care unit discharge between 2005 and 2013 BMC Cancer 2021 21 9 10.1186/s12885-020-07706-3 33402107
Gheerbrant H, Timsit J-F, Terzi N, Ruckly S, Laramas M, Levra MG, et al. Factors associated with survival of patients with solid Cancer alive after intensive care unit discharge between 2005 and 2013. BMC Cancer. 2021;21:9.33402107 10.1186/s12885-020-07706-3
16. Gonzalez F Starka R Ducros L Bisbal M Chow-Chine L Servan L Critically ill metastatic cancer patients returning home after unplanned ICU stay: an observational, multicentre retrospective study Ann Intensive Care 2023 13 73 10.1186/s13613-023-01170-5 37605072
Gonzalez F, Starka R, Ducros L, Bisbal M, Chow-Chine L, Servan L, et al. Critically ill metastatic cancer patients returning home after unplanned ICU stay: an observational, multicentre retrospective study. Ann Intensive Care. 2023;13:73.37605072 10.1186/s13613-023-01170-5
17. Azoulay E Afessa B The intensive care support of patients with malignancy: do everything that can be done Intensive Care Med 2006 32 3 5 10.1007/s00134-005-2835-6 16308682
Azoulay E, Afessa B. The intensive care support of patients with malignancy: do everything that can be done. Intensive Care Med. 2006;32:3–5.16308682 10.1007/s00134-005-2835-6
18. West HJ Jin JO JAMA Oncology Patient Page. Performance status in patients with Cancer JAMA Oncol 2015 1 998 10.1001/jamaoncol.2015.3113 26335750
West HJ, Jin JO. JAMA Oncology Patient Page. Performance status in patients with Cancer. JAMA Oncol. 2015;1:998.26335750 10.1001/jamaoncol.2015.3113
19. García de Herreros M Laguna JC Padrosa J Barreto TD Chicote M Font C Characterisation and outcomes of patients with solid organ malignancies admitted to the Intensive Care Unit: Mortality and Impact on Functional Status and Oncological Treatment Diagnostics (Basel) 2024 14 730 10.3390/diagnostics14070730 38611643
García de Herreros M, Laguna JC, Padrosa J, Barreto TD, Chicote M, Font C, et al. Characterisation and outcomes of patients with solid organ malignancies admitted to the Intensive Care Unit: Mortality and Impact on Functional Status and Oncological Treatment. Diagnostics (Basel). 2024;14:730.38611643 10.3390/diagnostics14070730
20. Tipping CJ Harrold M Holland A Romero L Nisbet T Hodgson CL The effects of active mobilisation and rehabilitation in ICU on mortality and function: a systematic review Intensive Care Med 2017 43 171 83 10.1007/s00134-016-4612-0 27864615
Tipping CJ, Harrold M, Holland A, Romero L, Nisbet T, Hodgson CL. The effects of active mobilisation and rehabilitation in ICU on mortality and function: a systematic review. Intensive Care Med. 2017;43:171–83.27864615 10.1007/s00134-016-4612-0
21. TEAM Study Investigators and the ANZICS Clinical Trials GroupHodgson CL Bailey M Bellomo R Brickell K Broadley T Early active mobilization during mechanical ventilation in the ICU N Engl J Med 2022 387 1747 58 10.1056/NEJMoa2209083 36286256
TEAM Study Investigators and the ANZICS Clinical Trials Group, Hodgson CL, Bailey M, Bellomo R, Brickell K, Broadley T, et al. Early active mobilization during mechanical ventilation in the ICU. N Engl J Med. 2022;387:1747–58.36286256 10.1056/NEJMoa2209083
22. Gautheret N Bommier C Mabrouki A Souppart V Bretaud AS Ghrenassia E Feasibility and safety of active physiotherapy in the Intensive Care Unit for intubated patients with malignancy J Rehabil Med 2023 55 jrm00299 10.2340/jrm.v54.736 36017667
Gautheret N, Bommier C, Mabrouki A, Souppart V, Bretaud AS, Ghrenassia E, et al. Feasibility and safety of active physiotherapy in the Intensive Care Unit for intubated patients with malignancy. J Rehabil Med. 2023;55:jrm00299.36017667 10.2340/jrm.v54.736
23. Elliott D McKinley S Alison J Aitken LM King M Leslie GD Health-related quality of life and physical recovery after a critical illness: a multi-centre randomised controlled trial of a home-based physical rehabilitation program Crit Care 2011 15 R142 10.1186/cc10265 21658221
Elliott D, McKinley S, Alison J, Aitken LM, King M, Leslie GD, et al. Health-related quality of life and physical recovery after a critical illness: a multi-centre randomised controlled trial of a home-based physical rehabilitation program. Crit Care. 2011;15:R142.21658221 10.1186/cc10265
24. Søgaard M Thomsen RW Bossen KS Sørensen HT Nørgaard M The impact of comorbidity on cancer survival: a review Clin Epidemiol 2013 5 3 29 10.2147/CLEP.S47150 24227920
Søgaard M, Thomsen RW, Bossen KS, Sørensen HT, Nørgaard M. The impact of comorbidity on cancer survival: a review. Clin Epidemiol. 2013;5:3–29.24227920 10.2147/CLEP.S47150
25. Ravasco P Nutrition in Cancer patients J Clin Med 2019 8 1211 10.3390/jcm8081211 31416154
Ravasco P. Nutrition in Cancer patients. J Clin Med. 2019;8:1211.31416154 10.3390/jcm8081211
26. Rodríguez-Cañamero S Cobo-Cuenca AI Carmona-Torres JM Pozuelo-Carrascosa DP Santacruz-Salas E Rabanales-Sotos JA Impact of physical exercise in advanced-stage cancer patients: systematic review and meta-analysis Cancer Med 2022 11 3714 27 10.1002/cam4.4746 35411694
Rodríguez-Cañamero S, Cobo-Cuenca AI, Carmona-Torres JM, Pozuelo-Carrascosa DP, Santacruz-Salas E, Rabanales-Sotos JA, et al. Impact of physical exercise in advanced-stage cancer patients: systematic review and meta-analysis. Cancer Med. 2022;11:3714–27.35411694 10.1002/cam4.4746
27. Dyba T Randi G Bray F Martos C Giusti F Nicholson N The European cancer burden in 2020: incidence and mortality estimates for 40 countries and 25 major cancers Eur J Cancer 2021 157 308 47 10.1016/j.ejca.2021.07.039 34560371
Dyba T, Randi G, Bray F, Martos C, Giusti F, Nicholson N, et al. The European cancer burden in 2020: incidence and mortality estimates for 40 countries and 25 major cancers. Eur J Cancer. 2021;157:308–47.34560371 10.1016/j.ejca.2021.07.039
28. Ruud Kjær EK Jensen JS Jakobsen KK Lelkaitis G Wessel I von Buchwald C The impact of Comorbidity on Survival in patients with Head and Neck squamous cell carcinoma: a Nationwide Case-Control Study spanning 35 years Front Oncol 2020 10 617184 10.3389/fonc.2020.617184 33680938
Ruud Kjær EK, Jensen JS, Jakobsen KK, Lelkaitis G, Wessel I, von Buchwald C, et al. The impact of Comorbidity on Survival in patients with Head and Neck squamous cell carcinoma: a Nationwide Case-Control Study spanning 35 years. Front Oncol. 2020;10:617184.33680938 10.3389/fonc.2020.617184
29. Kawakita D Abdelaziz S Chen Y Rowe K Snyder J Fraser A Adverse respiratory outcomes among head and neck cancer survivors in the Utah Cancer survivors Study Cancer 2020 126 879 85 10.1002/cncr.32617 31721181
Kawakita D, Abdelaziz S, Chen Y, Rowe K, Snyder J, Fraser A, et al. Adverse respiratory outcomes among head and neck cancer survivors in the Utah Cancer survivors Study. Cancer. 2020;126:879–85.31721181 10.1002/cncr.32617
30. de Freitas ICL de Assis DM Amendola CP Russo D da Moraes S de Caruso APP Characteristics and short-term outcomes of patients with esophageal cancer with unplanned intensive care unit admissions: a retrospective cohort study Rev Bras Ter Intensiva 2020 32 229 34 10.5935/0103-507X.20200041 32667448
de Freitas ICL, de Assis DM, Amendola CP, Russo D, da Moraes S, de Caruso APP. Characteristics and short-term outcomes of patients with esophageal cancer with unplanned intensive care unit admissions: a retrospective cohort study. Rev Bras Ter Intensiva. 2020;32:229–34.32667448 10.5935/0103-507X.20200041
31. Rathi NK Haque SA Morales F Kaul B Ramirez R Ovu S Variability in triage practices for critically ill cancer patients: a randomized controlled trial J Crit Care 2019 53 18 24 10.1016/j.jcrc.2019.05.012 31174172
Rathi NK, Haque SA, Morales F, Kaul B, Ramirez R, Ovu S, et al. Variability in triage practices for critically ill cancer patients: a randomized controlled trial. J Crit Care. 2019;53:18–24.31174172 10.1016/j.jcrc.2019.05.012
