Weaning outcome of solid cancer patients requiring mechanical ventilation in the intensive care unit

Journal of the Formosan Medical Association (2019) 118, 995e1004

Available online at www.sciencedirect.com

ScienceDirect journal homepage: www.jfma-online.com

Original Article

Weaning outcome of solid cancer patients requiring mechanical ventilation in the intensive care unit Emily Han-Chung Hsiue a,b, Pei-Lin Lee c,d,e,*, Yung-Hsuan Chen c, Ting-Hui Wu a,f, Chiao-Feng Cheng c, Keng-Man Cheng a, Po-Chun Yang a, Hsing-Wu Chen a, Pei-Yu Lin c, Dai-Lung Chiang g, Huey-Dong Wu h, James Chih-Hsin Yang a,i,j,k, Chong-Jen Yu c,d a Department of Oncology, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei, 100, Taiwan b Cellular and Molecular Medicine Program, Johns Hopkins School of Medicine, Suite 2-103, 1830 East Monument St, Baltimore, MD, 21205, USA c Department of Internal Medicine, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei, 100, Taiwan d Center of Sleep Disorder, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei, 100, Taiwan e Center for Electronics Technology Integration, National Taiwan University Hospital, No. 7, ChungShan South Road, Taipei, 100, Taiwan f Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA g Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No.1, Sec.4, Roosevelt Road, Taipei, Taiwan h Department of Integrated Diagnostics and Therapeutics, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei, 100, Taiwan i Department of Medical Research, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei, 100, Taiwan j Graduate Institute of Oncology, National Taiwan University College of Medicine, No. 1, Sec. 1, Ren-Ai Rd, 100, Taipei, Taiwan k National Taiwan University Cancer Center, No. 1, Sec. 1, Ren-Ai Rd, Taipei, 100, Taiwan

Received 11 October 2018; received in revised form 22 January 2019; accepted 20 February 2019

* Corresponding author. Department of Internal Medicine, Center of Sleep Disorder, National Taiwan University Hospital, Taipei, Taiwan, No. 7, Chung-Shan South Road, Taipei, 100, Taiwan. Fax: þ886 2 23582867. E-mail address: [email protected] (P.-L. Lee). https://doi.org/10.1016/j.jfma.2019.02.007 0929-6646/Copyright ª 2019, Formosan Medical Association. Published by Elsevier Taiwan LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

996

KEYWORDS Cancer; Intensive care unit; Mechanical ventilation; Weaning

E.H.-C. Hsiue et al.

Background: Whether the weaning outcome of solid cancer patients receiving mechanical ventilation (MV) in the intensive care unit (ICU) is comparable to that in non-cancer patients is unknown. The aim of this study was to compare the weaning outcomes between noncancer patients and patients with different types of cancer. Methods: We studied patients requiring MV during ICU stay for medical reasons between 2012 and 2014. Cancer patients were grouped into those with lung cancer (LC), head and neck cancer (HNC), hepatocellular carcinoma (HCC), and other cancers (OC). The primary endpoint was successful weaning at day 90 after the initiation of MV, and the main secondary endpoints were 28-day and 90-day mortality after ICU admission. Results: Five hundred and eighteen patients with solid cancers and 1362 non-cancer patients were recruited. The rate of successful weaning at day 90 was 57.9% in cancer patients, which was lower than 68.9% in non-cancer patients (p < 0.001). Compared to non-cancer patients, LC was associated with a lower probability of weaning at day 90 (hazard ratio 0.565, 95% CI 0.446 to 0.715), while HNC, HCC, and OC had similar probabilities. The 28-day and 90-day mortality rates were higher in cancer patients than in non-cancer patients (45.2% vs. 29.4%, and 65.6% vs. 37.7%, respectively, both p < 0.001). Conclusion: Among mechanically ventilated patients in the ICU, those with LC were associated with a lower probability of weaning at day 90 compared to non-cancer patients. Copyright ª 2019, Formosan Medical Association. Published by Elsevier Taiwan LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).

Introduction Advances in anticancer therapy have led to improved survival in patients with solid cancers.1 Cancer patients may develop life-threatening complications associated with their underlying malignancy or treatments. As a consequence, the number of cancer patients requiring intensive care unit (ICU) admission is rising.2 It has been estimated that one in 20 cancer patients require admission to an ICU within two years of diagnosis.3 Currently, cancer patients account for 15%e20% of all patients admitted to the ICU.4,5 Acute respiratory failure is the leading cause of ICU admission in cancer patients.6 The rate of mechanical ventilation (MV) in patients with solid cancers has been reported to range from 54% to 72%,6e8 and to be up to 90% in those with lung cancer (LC) or head and neck cancer (HNC) in the ICU.9,10 Recent studies have reported that 10.6% of all patients with prolonged MV (>21 days) had underlying malignancies, and that the incidence of prolonged MV among cancer patients is 10.4 per 100 ICU admissions.11,12 While the MV outcomes of patients with LC have been well described, they have rarely been studied in a large cohort of patients with solid cancers other than LC.12 The incidence rate of hepatocellular carcinoma (HCC) in Taiwan is approximately four-fold higher than the worldwide average.13,14 HCC patients may need critical care for both complications related to tumor progression and decompensated liver function.15 Beyond HCC, Taiwan is also an endemic region for HNC, with an incidence rate of oral cancer that is among the highest in the world.13,14 HNC patients may be admitted to an ICU due to a compromised airway caused by tumors and surgical procedures. The intensive care of HNC patients, however, has rarely been studied outside postsurgical settings.10,16 Earlier studies have reported a higher mortality rate in patients with cancer than in non-cancer patients,17 although

recent studies have shown that the survival of critically ill cancer patients has improved and may be non-inferior to that of non-cancer patients.18e23 However, most of these studies have included heterogeneous patient populations admitted to the ICU due to elective procedures, surgery, or medical reasons. Thus, it remains unclear whether the outcome of patients with solid cancers other than LC differs from that in non-cancer patients admitted to the ICU for medical reasons.7,19,22e26 We hypothesized that the MV outcomes and survival in cancer patients other than those with LC may be non-inferior to non-cancer patients admitted to the ICU for medical reasons. Therefore, the aims of this study were to compare rates of successful weaning at day 90, and mortality at day 28 and day 90 between non-cancer patients and patients with different types of cancer, and to identify the predictors of these outcomes.

Patients and methods Study setting This retrospective study was conducted at the 44-bed medical intensive care unit (MICU) of National Taiwan University Hospital (NTUH), a 2000-bed tertiary referral center in northern Taiwan. Decisions to admit individual patients to the ICU were based on the clinical judgment of ward physicians and intensivists. The Institutional Review Board of NTUH approved the study (No. 201501033RINB).

Patients We reviewed all adult patients (18 years) consecutively admitted to the ICU from January 1st, 2012 to December 31st, 2014 who received MV for >24 h through an endotracheal or tracheostomy tube. Patients who received non-

Weaning outcome of solid cancer patients requiring MV in ICU invasive ventilation (NIV) were excluded. For the patients with multiple ICU admissions, only the first admission was taken into account. Solid cancer patients and non-cancer patients were included. Patients with solid cancers were defined as those with a pathological diagnosis of cancer before ICU admission, and those with active disease or complete remission for <5 years. A pathological diagnosis was not required for HCC if it was diagnosed clinically according to international guidelines.27 Patients were excluded if they had hematologic malignancies or were admitted for routine postoperative care. All of the enrolled patients were followed until death or December 31st, 2015, whichever came first. Table 1

997

Data collection The following data were collected from the medical records for all patients: demographics; the Acute Physiology and Chronic Health Evaluation II (APACHE II) score; comorbidities including cirrhosis, diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), end-stage renal disease (ESRD), and congestive heart failure (CHF); cause of ICU admission; MV duration; ICU and hospital length of stay (LOS); and interventions during ICU admission including vasopressor administration and initiation of renal replacement therapy. The five categories of cause of ICU admission and the conditions each category includes is as follows: 1)

Characteristics of the non-cancer and cancer patients with different cancer types admitted to the ICU.

e

Age, median (IQR ) Male APACHE IIf, mean  SD Cancer features Metastasis Uncontrolled disease Anti-cancer therapy <30 days Comorbidity Cirrhosis DMg COPDh ESRDi CHFj Cause of admission Respiratory failure Septic shock Cardiovascular GIk bleeding Miscellaneous ICU Intervention Vasopressors RRTl

P-value LCa

HNCb

HCCc

OCd

(N Z 153)

(N Z 97)

(N Z 53)

(N Z 215)

68.0 (58.0e75.5) 98 (64.1) 23.8  8.0

57.0 (49.0e65.8) 80 (82.5) 24.3  7.8

69.0 (59.0e80.5) 32 (60.4) 25.6  8.9

65.0 <0.001m (55.0e74.0) 115 (53.5) <0.001m 26.9  8.6 0.002n

e e e

130 (85.0) 121 (79.1) 92 (60.1)

47 (48.5) 65 (68.0) 58 (60.8)

13 (24.5) 33 (62.3) 11 (20.8)

146 (67.9) 148 (68.8) 117 (54.4)

<0.001o 0.052 <0.001p

0.199 <0.001 0.001 0.001 <0.001 <0.009

2 (1.3) 36 (23.5) 19 (12.4) 4 (2.6) 8 (5.2)

6 (6.2) 22 (22.7) 3 (3.1) 1 (1.0) 1 (1.0)

38 (71.7) 19 (35.8) 1 (1.9) 1 (1.9) 1 (1.9)

7 (3.3) 58 (27.0) 10 (4.7) 10 (4.7) 14 (6.5)

<0.001q 0.282 0.003r 0.321 0.133 <0.001

132 (86.3) 9 (5.9) 3 (2.0) 0 (0.0) 9 (5.9)

63 (64.9) 12 (12.4) 3 (3.1) 4 (4.1) 15 (15.5)

19 (35.8) 15 (28.3) 3 (5.7) 12 (22.6) 4 (7.5)

128 (59.5) 53 (24.7) 10 (4.7) 6 (2.8) 18 (8.4)

118 (77.1) 18 (11.8)

71 (73.2) 9 (9.3)

40 (75.5) 18 (34.0)

155 (72.1) 47 (21.9)

Non-Cancer

All cancer

(N Z 1362)

(N Z 518)

73.0 (58.0e82.0) 832 (61.1) 23.5  8.8

65.0 <0.001 (55.0e75.0) 325 (62.7) 0.487 25.4  8.4 <0.001

e e e

336 (64.9) 367 (71.0) 188 (36.4)

114 (8.4) 482 (35.4) 160 (11.7) 96 (7.0) 247 (18.1)

53 (10.2) 135 (26.1) 33 (6.4) 16 (3.1) 24 (4.6)

866 (63.6) 200 (14.7) 113 (8.3) 56 (4.1) 127 (9.3)

342 (66.0) 89 (17.2) 19 (3.7) 22 (4.2) 46 (8.9)

846 (62.1) 272 (20.0)

384 (74.1) 92 (17.8)

<0.001 0.306

P-value

0.735 <0.001s

Data are presented as number (percentage) unless otherwise specified. a LC, lung cancer. b HNC, head and neck cancer. c HCC, hepatocellular carcinoma. d OC, other cancer. e IQR, interquartile range. f APACHE II, Acute Physiology and Chronic Health Evaluation II score. g DM, diabetes mellitus. h COPD, chronic obstructive pulmonary disease. i ESRD, end-stage renal disease. j CHF, congestive heart failure. k GI, gastrointestinal. l RRT, renal replacement therapy. m HNC vs. LC, HNC vs. HCC, HNC vs. OC, pairwise comparison Bonferroni-adjusted P-value <0.0083. n OC vs. LC, HNC vs. OC, pairwise comparison Bonferroni-adjusted P-value <0.0083 pairwise comparison Bonferroni-adjusted P-value <0.0083. o HNC vs. LC, HCC vs. LC, OC vs. LC, HNC vs. HCC, HNC vs. OC, HCC vs. OC, pairwise comparison Bonferroni-adjusted P-value <0.0083. p HCC vs. LC, HNC vs. HCC, pairwise comparison Bonferroni-adjusted P-value <0.0083. q HCC vs. LC, HNC vs. HCC, HCC vs. OC, pairwise comparison Bonferroni-adjusted P-value <0.0083. r OC vs. LC, pairwise comparison Bonferroni-adjusted P-value <0.0083. s HCC vs. LC, HNC vs. HCC, HNC vs. OC, pairwise comparison Bonferroni-adjusted P-value <0.0083.

998

E.H.-C. Hsiue et al.

respiratory failure: pneumonia, chronic obstructive pulmonary disease with acute exacerbation, pulmonary embolism, hemoptysis, airway obstruction, pneumothorax, acute lung edema, hemoptysis; 2) Septic shock; 3) cardiovascular: out of hospital cardiac arrest, in-hospital cardiac arrest, pulmonary edema, ST-elevation myocardial information, non-ST-elevation myocardial infarction; 4) GI bleeding: gastric bleeding, intestinal bleeding, esophageal variceal bleeding; 5) miscellaneous: tumor bleeding, seizure, stroke, intracerebral hemorrhage, diabetic ketoacidosis, hyperosmolar hyperglycemic state. For the solid cancer patients, the following data were recorded: cancer type classified by the primary site of origin, presence of metastasis, use of systemic anticancer therapy <30 days before ICU admission, and cancer status at ICU admission. In patients with more than one cancer types, the cancer that was being actively treated or followed at the time of ICU admission was used for cancer type classification. Cancer status was classified as: (1) controlled disease, if stable or responsive disease was documented <30 days before ICU admission, or if the patient had been in complete remission for < 5 years; or (2) Table 2

uncontrolled disease, if cancer was diagnosed <30 days prior to ICU admission, or if progressive disease was documented <30 days before ICU admission.

Outcome measures The primary endpoint was successful weaning at day 90 after MV. Successful weaning was defined as liberation from MV for >24 h while alive. A study using Taiwan’s National Health Insurance Research Database showed that the probabilities of reinstituting MV after one and two days of ventilator liberation were 2% and 4%, respectively.28 We considered the difference between 2% and 4% to be non-clinically significant and chose 24-hr liberation from ventilator as the definition of successful weaning. The main secondary endpoints were 28day and 90-day mortality rates. Other secondary outcomes included: 1) median MV-free days at day 28 and day 90, 2) receiving tracheostomy during ICU stay, 3) media ICU LOS, and 4) median hospital LOS. MV-free days at day 28 and day 90 was a composite endpoint defined as the number of days without MV during the first 28-day and 90-day periods after starting MV, respectively. If a patient died within 28 day or 90

Primary and secondary outcomes.

Primary Successful weaning at day 90, n (%)e Secondary Mortality at 28 days, n (%)e Mortality at 90 days, n (%)e Median MV-free day to day 28, dayf,g Median MV-free day to day 90, dayf,g Tracheostomy, n (%)h ICU median length of stay, dayg Hospital median length of stay, dayg

Non-Cancer

LCa

HNCb

HCCc

OCd

(N Z 1362)

(N Z 153)

(N Z 97)

(N Z 53)

(N Z 215)

939 (68.9)

75 (49.0)

62 (63.9)

33 (62.3)

130 (60.5)

<0.001i

401 (29.4)

72 (47.1)

38 (39.2)

26 (49.1)

98 (45.6)

<0.001j

513 (37.7)

109 (71.2)

55 (56.7)

35 (66.0)

141 (65.6)

<0.001k

13.0 (0e22.0)

0 (0e14.0)

1.0 (0e22.0)

0 (0e19.0)

0 (0e19.0)

<0.001l

72.0 (0e83.0)

0 (0e69.0)

44.0 (0e82.0)

0 (0e78.0)

0 (0e78.0)

<0.001m

138 (10.1) 13.0 (8.0e19.0)

21 (13.7) 16.0 (9.0e24.0)

17 (17.5) 12.0 (7.0e21.0)

4 (7.5) 20 (9.3) 11.0 (5.0e17.5) 12.0 (7.0e19.0)

P-value

0.126 0.020n

24.0 (14.0e44.0) 26.0 (11.0e40.5) 20.0 (12.0e37.0) 17.0 (8.0e47.5) 23.0 (11.0e54.0) 0.309

Data are presented as mean (95% CI) (for time to successful weaning) or median (IQR) or number (percentage). a LC, lung cancer. b HNC, head and neck cancer. c HCC, hepatocellular carcinoma. d OC, other cancer. e Successful weaning and mortality at day 90 were analyzed using KaplaneMeier analysis. f MV-free days to day 28 and day 90 was defined as the number of days without MV during the first 28-day and 90-day period after ICU admission, respectively. If a patient died while using MV or remained MV-dependent for more than 28 or 90 days, MV-free days was defined as 0. g MV-free days, and ICU and hospital median length of stay were analyzed using the KruskaleWallis test. h Tracheostomy was analyzed with the chi-square test and Bonferroni correction. i LC vs. non-cancer, HCC vs. LC, OC vs. LC, pairwise comparison Bonferroni-adjusted P-value<0.005. j LC vs. non-cancer, HCC vs. non-cancer, OC vs. non-cancer, pairwise comparison Bonferroni-adjusted P-value<0.005. k LC vs. non-cancer, HNC vs. non-cancer, HCC vs. non-cancer, OC vs. non-cancer, pairwise comparison Bonferroni-adjusted Pvalue<0.005. l LC vs. non-cancer, OC vs. non-cancer, pairwise comparison Bonferroni-adjusted P-value<0.005. m LC vs. non-cancer, HCC vs. non-cancer, OC vs. non-cancer, pairwise comparison Bonferroni-adjusted P-value<0.005. n LC vs. non-cancer, OC vs. LC, pairwise comparison Bonferroni-adjusted P-value<0.005.

Weaning outcome of solid cancer patients requiring MV in ICU Table 3 Prognostic factors for successful weaning at day 90 in all patients. Successful weaning at D90, HRa (95% CIb) Univariate Cancer type Non-cancer Reference LCc 0.553 (0.437e0.699) 0.868 HNCd (0.671e1.122) 1.001 HCCe (0.707e1.416) 0.889 OCf (0.740e1.068) APACHE IIg 0.978 (0.972e0.985) Age 0.997 (0.994e1.001) Gender 1.072 (0.956e1.203) Cirrhosis 0.894 (0.724e1.104) 1.082 DMh (0.963e1.216) 1.302 COPDi (1.099e1.543) 1.056 ESRDj (0.843e1.323) 1.027 CHFk (0.88e1.198) Vasopressors 0.524 (0.468e0.587) 0.579 RRTl (0.49e0.684)

P-value Multivariate

P-value

<0.001

<0.001

Reference <0.001 0.565 (0.446e0.715) 0.279 0.907 (0.700e1.175) 0.996 1.212 (0.854e1.719) 0.209 0.945 (0.785e1.136) <0.001 0.987 (0.980e0.994) 0.146

<0.001 0.459 0.281 0.545 <0.001

999 KruskaleWallis test with the Bonferroni post-hoc method were used as appropriate. The times to successful weaning and mortality were analyzed using the KaplaneMeier method and compared between groups using a log-rank test with Bonferroni correction. Cox proportional hazard analysis was used to compare hazards between non-cancer patients and patients with different types of cancer, and cancer type, cancer status (metastasis, uncontrolled disease, anticancer therapy <30 days), and variables with pvalues <0.1 in univariate analysis were used as covariates. The results of Cox regression were presented as hazard ratio (HR) and 95% confidence interval (CI). A two-sided pvalue <0.05 was considered to be statistically significant. All statistical analyses were conducted using SPSS version 23 (SPSS, Chicago, IL) or R version 3.3.5.

Results Patient characteristics

0.232 0.299 0.183 0.002

1.105 0.263 (0.928e1.315)

0.638 0.739 <0.001 0.601 <0.001 (0.533e0.677) <0.001 0.667 <0.001 (0.561e0.793)

a

HR, hazard ratio. CI, confidence interval. c LC, lung cancer. d HNC, head and neck cancer. e HCC, hepatocellular carcinoma. f OC, other cancer. g APACHE II, Acute Physiology and Chronic Health Evaluation II score. h DM, diabetes mellitus. i COPD, chronic obstructive pulmonary disease. j ESRD, end-stage renal disease. k CHF, congestive heart failure. l RRT, renal replacement therapy. b

Between 2012 and 2014, 518 solid cancer patients and 1362 non-cancer patients received MV in the ICU at NTUH (Supplementary Fig. 1). Over 60% of the patients in both groups were admitted due to respiratory failure (Table 1), with pneumonia being the predominant etiologies in both groups (cancer patients 85.7%, non-cancer patients 86.7%, Supplementary Table 1). According to a prospective study conducted at our hospital during the same study period, the estimated ARDS rate was 18.8% in the cancer group, and 14.9% in the non-cancer group (Ruan et al. unpublished data). Compared to non-cancer patients, those with cancer were significantly younger and had fewer co-morbidities except for cirrhosis, higher APACHE II score, and greater use of vasopressors. The median follow-up periods of cancer and non-cancer patients were 33.0 days (IQR 12.0e100.0) and 76.0 days (IQR 17.0e661.0), respectively. LC (29.6%), HNC (18.7%), and HCC (10.3%) were the most common cancer types (Supplementary Table 2). Fifteen patients had more than one cancers (Supplementary Table 3). Among cancer patients, 64.9% had metastasis and 71.0% had uncontrolled disease on ICU admission. Compared to HNC, HCC, and other cancers (OC), patients with LC had the highest frequencies of metastasis and uncontrolled disease (Table 1). Among HCC patients, 71.7% had documented cirrhosis and 22.6% were admitted due to gastrointestinal bleeding, a common complication of decompensated liver function.

Primary outcome day (no matter they are on MV or not) or remained MVdependent for more than 28 or 90 days, MV-free days was defined as 0.29

Statistical analysis Continuous variables were expressed as mean (standard deviation [SD]) or median (interquartile range [IQR]), and categorical variables were expressed as number (percentage). The Student’s t-test, Wilcoxon-Mann-Whitney U test, chi-square test with Bonferroni correction, and the

The rate of successful weaning at day 90 was 68.9% in non-cancer patients and 57.9% in cancer patients. KaplaneMeier analysis showed that the mean number of days to successful weaning was 21.2 (95% CI 19.5e22.9) in non-cancer patients and 27.0 days (95% CI 23.6 to 30.4) in cancer patients. Among cancer patients, mean duration to successful weaning was 37.3 days (95% CI 30.1e44.6) in patients with LC, 21.0 days (95% CI 16.8e25.2) in those with HNC, 19.6 days (95% CI 12.3e26.9) in those with HCC, and 23.4 days (95% CI 18.7e28.2) in those with OC (log-rank p < 0.001). Compared to non-cancer patients, cancer patients had a

1000 lower probability of weaning, which was primarily driven by the poor weaning outcome of LC (Tables 2 and 3, Fig. 1, Supplementary Table 4). After adjusting for APACHE II score, chronic obstructive pulmonary disease, vasopressor use, and renal replacement therapy (RRT), LC was still associated with a lower probability of weaning at day 90 compared to non-cancer patients. On the other hand, HNC, HCC, and OC had similar probabilities of weaning to non-cancer patients (Table 3). Among cancer patients, after adjusting for vasopressor use and RRT, cancer features including cancer type and cancer status significantly influence the probability of weaning at day 90. Compared to patients with LC, those with HNC, HCC, and OC had higher probabilities of weaning. Metastasis was associated with a lower probability of weaning (Supplementary Table 4).

Main secondary outcomes The 28-day mortality rate was 45.2% in cancer patients and 29.4% in non-cancer patients. KaplaneMeier analysis showed that the probability of mortality at day 28 was higher in cancer patients compared to non-cancer patients, especially for those with LC, HCC and OC. Cancer patients also had a higher probability of mortality at day 90 than non-cancer patients, and all types of cancer were associated with a higher mortality (Tables 2 and 4, Fig. 2, Supplementary Table 5). After adjusting for APACHE II score, age, comorbidities, vasopressor use, and RRT, patients with LC and OC were associated with higher probabilities of mortality at day 28 than non-cancer patients (Table 4). In addition, patients

E.H.-C. Hsiue et al. with LC, HNC, and OC had higher probabilities of mortality at day 90 compared to non-cancer patients (Table 4). Among cancer patients, after adjusting for APACHE II score, vasopressor use, and RRT, the type of cancer did not affect the mortality at either 28 days or 90 days, while metastasis was associated with higher probabilities of mortality at day 28 and day 90. Uncontrolled disease was associated with a higher probability of mortality at day 90 (Supplementary Table 5).

Other secondary outcomes Compared to non-cancer patients, patients with LC and OC had fewer MV-free days to day 28 and day 90, while patients with HNC had similar MV-free days. Patients with LC also had a longer median ICU stay than the non-cancer patients and those with OC. Tracheostomy rates were similar between non-cancer patients and those with any type of cancer (Table 2). The weaning rate after receiving tracheostomy was also similar between cancer (42/62, 67.7%) and non-cancer patients (102/138, 74.0%; p Z 0.466).

Discussion Even though mortality in cancer patients requiring ventilatory support has been extensively investigated,23,30,31 only a few studies have evaluated the weaning outcomes in this population.32e34 In this large retrospective study, we demonstrated that patients with LC were associated with a lower probability of weaning at day 90 compared to noncancer patients, while those with HNC, HCC, and OC had

Figure 1 KaplaneMeier estimate of probability of successful weaning at day 90 after mechanical ventilation. a LC, lung cancer. b HNC, head and neck cancer. c HCC, hepatocellular carcinoma. d OC, other cancer.

Weaning outcome of solid cancer patients requiring MV in ICU Table 4

1001

Prognostic factors for 28-day and 90-day mortality in all patients. 28-day mortality, HRa (95% CIb) Univariate

Cancer type Non-cancer LCc HNCd HCCe OCf APACHE IIg Age Gender Cirrhosis DMh COPDi ESRDj CHFk Vasopressors RRTl a b c d e f g h i j k l

P-value

Multivariate

<0.001 Reference 1.723 (1.341e2.215) 1.351 (0.968e1.884) 1.905 (1.281e2.833) 1.699 (1.362e2.119) 1.046 (1.037e1.055) 0.995 (0.991e1.000) 1.000 (0.852e1.173) 1.776 (1.411e2.234) 0.756 (0.636e0.899) 0.602 (0.443e0.818) 0.675 (0.459e0.993) 0.796 (0.628e1.009) 3.011 (2.451e3.699) 2.710 (2.298e3.196)

<0.001 0.077 0.001 <0.001 <0.001 0.043

90-day mortality, HR (95% CI) P-value <0.001

Reference 1.689 (1.304e2.187) 1.264 (0.899e1.777) 1.225 (0.799e1.879) 1.391 (1.105e1.750) 1.033 (1.024e1.043) 0.996 (0.991e1.002)

<0.001 0.177 0.351 0.005 <0.001 0.170

0.996 <0.001 0.002 0.001 0.046 0.060 <0.001 <0.001

Univariate

1.467 (1.137e1.894) 0.800 (0.668e0.959) 0.841 (0.613e1.154) 0.741 (0.499e1.100) 0.958 (0.749e1.227) 2.008 (1.685e2.588) 1.991 (1.667e2.377)

0.003 0.016 0.283 0.137 0.736 <0.001 <0.001

P-value

Multivariate

<0.001 Reference 2.180 (1.789e2.656) 1.637 (1.259e2.128) 2.025 (1.452e2.824) 2.032 (1.703e2.425) 1.042 (1.035e1.050) 0.997 (0.993e1.001) 0.979 (0.853e1.123) 1.784 (1.457e2.186) 0.764 (0.658e0.886) 0.609 (0.470e0.790) 0.778 (0.572e1.057) 0.806 (0.659e0.986) 2.662 (2.252e3.147) 2.492 (2.151e2.887)

<0.001 <0.001 <0.001 <0.001 <0.001

P-value <0.001

Reference 2.241 (1.810e2.775) 1.573 (1.186e2.086) 1.259 (0.869e1.825) 1.725 (1.423e2.091) 1.028 (1.020e1.036)

<0.001 0.002 0.223 <0.001 <0.001

0.128 0.762 <0.001 <0.001 <0.001

1.660 (1.324e2.081) 0.801 (0.688e0.933) 0.820 (0.629e1.070)

<0.001

0.988 (0.801e1.218) 1.875 (1.573e2.234) 1.971 (1.688e2.302)

0.907

0.004 0.143

0.108 0.036 <0.001 <0.001

<0.001 <0.001

HR, hazard ratio. CI, confidence interval. LC, lung cancer. HNC, head and neck cancer. HCC, hepatocellular carcinoma. OC, other cancer. APACHE II, Acute Physiology and Chronic Health Evaluation II score. DM, diabetes mellitus. COPD, chronic obstructive pulmonary disease. ESRD, end-stage renal disease. CHF, congestive heart failure. RRT, renal replacement therapy.

weaning outcomes similar to non-cancer patients despite of higher mortality rates. In addition, compared to the noncancer patients, those with LC and OC were independently associated with higher probabilities of mortality at both day 28 and day 90, while those with HNC were associated with a high probability of mortality at day 90. Moreover, among cancer patients, those with LC were independently associated with a lower probability of weaning at day 90 compared to those with other types of cancer, while the mortality rate was similar across all cancer types. These findings suggest that patients with HNC and HCC requiring MV should not be deferred from intensive care, while those with LC should be informed of the risks of prolonged MV before initiating MV.

Critically ill HNC patients have mainly been studied in the post-surgical setting, and the MV outcome of those admitted to the ICU for medical reasons are unclear.10,16,35 In our study, HNC patients had weaning outcomes similar to non-cancer patients, including the probability of successful weaning at day 90 and median MV-free days to day 28 and day 90. These results are consistent with a previous study in which HNC was among the cancer types with the lowest incidence of prolonged MV.12 HNC patients are often admitted to the ICU due to upper airway compromise caused by tumor growth or tumor bleeding, which can often be managed by tracheostomy and arterial embolization, respectively. The trend of a higher tracheostomy rate (17.7%) in the HNC patients may contribute to the non-

1002

E.H.-C. Hsiue et al.

Figure 2 KaplaneMeier estimate of probability of survival at day 90 after ICU admission. a LC, lung cancer. b HNC, head and neck cancer. c HCC, hepatocellular carcinoma. d OC, other cancer.

inferior MV outcomes. Moreover, to the best of our knowledge, the present study included the largest mechanically ventilated HCC patient cohort to date. Most HCC patients have cirrhosis and may require critical care for cirrhosisrelated complications. In addition to the non-inferior MV outcomes, both HNC and HCC patients had 28-day mortality rates similar to non-cancer patients after adjusting for APACHE II score, comorbidities, and treatment in the ICU. Taken together, we propose that ICU admission of patients with HNC and HCC should not be deferred, and that aggressive weaning should be considered after the initiation of MV. Our finding of poor MV outcomes in LC patients is in accordance with the findings of a Taiwan national registry study, in that LC patients had the highest incidence of prolonged MV among all cancer patients.12 Therefore, we suggest that LC patients being considered for ventilatory support in the ICU should be informed of the risks of prolonged MV before initiating MV. Our results showed that metastasis was predictive of MV outcomes in cancer patients. This is in contrast to the study by Vallot et al., in which cancer status did not affect weaning in mechanically ventilated cancer patients.34 However, the study by Vallot et al. was conducted more than a decade ago and included patients with both solid and hematological cancers, and the overall weaning rate was only 26% compared to 58% in the present study. It is possible that advances in support care have resulted in more effective control of acute illnesses, and that underlying disease status may now be a more prominent factor in determining MV liberation. There are several limitations to this study. First, detailed information regarding performance status, which has been identified as a significant prognostic factor in

several studies, was not available in our medical records.8,23 Second, although end-of-life decisions may affect patient outcome, we did not assess this impact due to the lack of relevant information in the electronic records. Third, although NIV has been reported to be associated with lower mortality in cancer patients who require ventilatory support, the present study did not investigate the association between NIV and outcomes.16 The heterogeneous indications for instituting NIV in cancer patients, ranging from support for conditions known to respond to NIV, facilitation of weaning, to simply a palliative measure, may result in a wide range of weaning outcomes. Therefore, we did not include NIV use. We also did not include high flow oxygen because it was not a common practice during the study period. A prospective study with predefined indications for NIV is needed to clarify the impact of NIV and high flow oxygen therapy.

Conclusions In this large retrospective study on patients requiring MV during ICU admission for medical reasons, we demonstrated that patients with LC, but not those with HNC or HCC, were associated with poorer weaning outcomes than non-cancer patients.

Funding This study was sponsored by the Ministry of Science and Technology Taiwan (MOST 103- 2314- Be 002- 139- MY3), National Taiwan University Hospital (NTUH 105- S2998, 107e19, 108-S4331), and Center for Electronic Technology Integration (NTU-107L900502) from The Featured Areas

Weaning outcome of solid cancer patients requiring MV in ICU Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.

Declarations of interest All authors declare that they have no conflicts of interest.

Acknowledgements The authors thank the Taiwan Clinical Trial Bioinformatics and Statistical Center, Training Center, and Pharmacogenomics Laboratory (funded by the National Research Program for Biopharmaceuticals [NRPB] at the National Science Council of Taiwan; NSC 102-2325-B-002-088) statistical assistance. The authors would also like to thank the Department of Medical Research of National Taiwan University Hospital for assistance in data collection and editing the manuscript. The authors would also like to thank Dr. Ming-Tzer Lin for assistance in processing the figures.

Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.jfma.2019.02.007.

References 1. Clegg LX, Li FP, Hankey BF, Chu K, Edwards BK. Cancer survival among US whites and minorities: a SEER (Surveillance, Epidemiology, and End Results) Program population-based study. Arch Intern Med 2002;162(17):1985e93. 2. Puxty K, McLoone P, Quasim T, Kinsella J, Morrison D. Survival in solid cancer patients following intensive care unit admission. Intensive Care Med 2014;40(10):1409e28. 3. 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(8): 1078e85. 4. Soares M, Bozza FA, Azevedo LC, Silva UV, Correa TD, Colombari F, et al. Effects of organizational characteristics on outcomes and resource use in patients with cancer admitted to intensive care units. J Clin Oncol : Off J Am Soc Clin Oncol 2016;34(27):3315e24. 5. Vincent JL, Marshall JC, Namendys-Silva SA, Francois B, MartinLoeches I, Lipman J, et al. Assessment of the worldwide burden of critical illness: the intensive care over nations (ICON) audit. Lancet Respir Med 2014;2(5):380e6. 6. Taccone FS, Artigas AA, Sprung CL, Moreno R, Sakr Y, Vincent JL. Characteristics and outcomes of cancer patients in European ICUs. Crit Care 2009;13(1):R15. 7. Azoulay E, Moreau D, Alberti C, Leleu G, Adrie C, Barboteu M, et al. Predictors of short-term mortality in critically ill patients with solid malignancies. Intensive Care Med 2000;26(12): 1817e23. 8. Staudinger T, Stoiser B, Mullner M, Locker GJ, Laczika K, Knapp S, et al. Outcome and prognostic factors in critically ill cancer patients admitted to the intensive care unit. Crit Care Med 2000;28(5):1322e8. 9. Andrejak C, Terzi N, Thielen S, Bergot E, Zalcman G, Charbonneau P, et al. Admission of advanced lung cancer patients to intensive care unit: a retrospective study of 76 patients. BMC Canc 2011;11:159.

1003 10. Soares M, Salluh JI, Toscano L, Dias FL. Outcomes and prognostic factors in patients with head and neck cancer and severe acute illnesses. Intensive Care Med 2007;33(11):2009e13. 11. Hung MC, Lu HM, Chen L, Hu FC, Chan SY, Yan YH, et al. Life expectancies and incidence rates of patients under prolonged mechanical ventilation: a population-based study during 1998 to 2007 in Taiwan. Crit Care 2011;15(2):R107. 12. Shih CY, Hung MC, Lu HM, Chen L, Huang SJ, Wang JD. Incidence, life expectancy and prognostic factors in cancer patients under prolonged mechanical ventilation: a nationwide analysis of 5,138 cases during 1998-2007. Crit Care 2013;17(4): R144. 13. Chiang CJ, Lo WC, Yang YW, You SL, Chen CJ, Lai MS. Incidence and survival of adult cancer patients in Taiwan, 2002-2012. J Formos Med Assoc 2016;115(12):1076e88. 14. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136(5):E359e86. 15. Aggarwal A, Ong JP, Younossi ZM, Nelson DR, Hoffman-Hogg L, Arroliga AC. Predictors of mortality and resource utilization in cirrhotic patients admitted to the medical ICU. Chest 2001; 119(5):1489e97. 16. Downey RJ, Friedlander P, Groeger J, Kraus D, Schantz S, Spiro R, et al. Critical care for the severely ill head and neck patient. Crit Care Med 1999;27(1):95e7. 17. Darmon M, Azoulay E. Critical care management of cancer patients: cause for optimism and need for objectivity. Curr Opin Oncol 2009;21(4):318e26. 18. Auclin E, Charles-Nelson A, Abbar B, Guerot E, Oudard S, Hauw-Berlemont C, et al. Outcomes in elderly patients admitted to the intensive care unit with solid tumors. Ann Intensive Care 2017;7(1):26. 19. Azoulay E, Soares M, Darmon M, Benoit D, Pastores S, Afessa B. Intensive care of the cancer patient: recent achievements and remaining challenges. Ann Intensive Care 2011;1(1):5. 20. Pene F, Percheron S, Lemiale V, Viallon V, Claessens YE, Marque S, et al. Temporal changes in management and outcome of septic shock in patients with malignancies in the intensive care unit. Crit Care Med 2008;36(3):690e6. 21. Rosa RG, Tonietto TF, Duso BA, Maccari JG, de Oliveira RP, Rutzen W, et al. Mortality of adult critically ill subjects with cancer. Respir Care 2017;62(5):615e22. 22. Soares M, Darmon M, Salluh JIF, Ferreira CG, Thiery G, Schlemmer B, et al. Prognosis of lung cancer patients with lifethreatening complications. Chest 2007;131(3):840e6. 23. Soares M, Salluh JI, Spector N, Rocco JR. Characteristics and outcomes of cancer patients requiring mechanical ventilatory support for >24 hrs. Crit Care Med 2005;33(3):520e6. 24. Heo SJ, Kim G, Lee CK, Chung KS, Choi HJ, Sohn J, et al. Prediction of short- and long-term survival for advanced cancer patients after ICU admission. Support Care Canc : Off J Multinatl Assoc Support Care Canc 2015;23(6):1647e55. 25. Sculier JP, Paesmans M, Markiewicz E, Berghmans T. Scoring systems in cancer patients admitted for an acute complication in a medical intensive care unit. Crit Care Med 2000;28(8): 2786e92. 26. Soares M, Caruso P, Silva E, Teles JM, Lobo SM, Friedman G, et al. Characteristics and outcomes of patients with cancer requiring admission to intensive care units: a prospective multicenter study. Crit Care Med 2010;38(1):9e15. 27. Heimbach JK, Kulik LM, Finn RS, Sirlin CB, Abecassis MM, Roberts LR, et al. AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology 2018;67(1):358e80. 28. Ruan SY, Teng NC, Wu HD, Tsai SL, Wang CY, Wu CP, et al. Durability of weaning success for liberation from invasive mechanical ventilation: an analysis of a nationwide Database. Am J Respir Crit Care Med 2017;196(6):792e5.

1004 29. Schoenfeld DA, Bernard GR, Network A. Statistical evaluation of ventilator-free days as an efficacy measure in clinical trials of treatments for acute respiratory distress syndrome. Crit Care Med 2002;30(8):1772e7. 30. Azevedo LCP, Caruso P, Silva UVA, Torelly AP, Silva E, Rezende E, et al. Outcomes for patients with cancer admitted to the ICU requiring ventilatory support: results from a prospective multicenter study. Chest 2014;146(2): 257e66. 31. Azoulay E, Alberti C, Bornstain C, Leleu G, Moreau D, Recher C, et al. Improved survival in cancer patients requiring mechanical ventilatory support: impact of noninvasive mechanical ventilatory support. Crit Care Med 2001; 29(3):519e25.

E.H.-C. Hsiue et al. 32. Ewer MS, Ali MK, Atta MS, Morice RC, Balakrishnan PV. Outcome of lung cancer patients requiring mechanical ventilation for pulmonary failure. J Am Med Assoc 1986;256(24):3364e6. 33. Lin YC, Tsai YH, Huang CC, Hsu KH, Wang SW, Tsao TC, et al. Outcome of lung cancer patients with acute respiratory failure requiring mechanical ventilation. Respir Med 2004;98(1):43e51. 34. Vallot F, Paesmans M, Berghmans T, Sculier JP. Leucopenia is an independent predictor in cancer patients requiring invasive mechanical ventilation: a prognostic factor analysis in a series of 168 patients. Support Care Canc : Off J Multinatl Assoc Support Care Canc 2003;11(4):236e41. 35. Godden DR, Patel M, Baldwin A, Woodwards RT. Need for intensive care after operations for head and neck cancer surgery. Br J Oral Maxillofac Surg 1999;37(6):502e5.