# Mortality of cancer patients with septic shock: A nation-based cohort analysis of 77,888 patients

Antoine Bianchi, Yann Brousse, Ines Lakbar, Vanessa Pauly, Veronica Orleans, Guillaume Fond, Gary Duclos, Laurent Zieleskiewicz, Djamel Mokart, Laurent Boyer, et al.

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Antoine Bianchi, Yann Brousse, Ines Lakbar, Vanessa Pauly, Veronica Orleans, et al. Mortality of cancer patients with septic shock: A nation-based cohort analysis of 77,888 patients. Anaesthesia Critical Care & Pain Medicine, 2025, 44 (5), pp.101557. 10.1016/j.accpm.2025.101557. hal-05089906

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# Mortality of cancer patients with septic shock: A nation-based cohort analysis of 77,888 patients

Antoine Bianchi¹, Yann Brousse², Ines Lakbar³, Vanessa Pauly⁴, Veronica Orleans⁴, Guillaume Fond², Gary Duclos¹, Laurent Zieleskiewicz¹, Djamel Mokart⁵, Laurent Boyer², Marc Leone⁶

¹ Aix-Marseille University, AP-HM, North Hospital, Department of Anaesthesia and Intensive Care Medicine, France.

² CERESS, Health Service Research and Quality of Life Centre, School of Medicine - La Timone Medical, Aix-Marseille University, France; Department of Medical Information and Public Health, AP-HM, Aix-Marseille University, France.

³ Critical Care and Anesthesia Department (DAR B), Hôpital Saint-Éloi, CHU de Montpellier, PhyMedExp, Université de Montpellier, Montpellier, France.

⁴ Department of Medical Information and Public Health, AP-HM, Aix-Marseille University, France.

⁵ Medical Surgical Intensive Care Unit, Institut Paoli Calmettes, Marseille, France.

⁶ Aix-Marseille University, AP-HM, North Hospital, Department of Anaesthesia and Intensive Care Medicine, France. Electronic address: marc.leone@ap-hm.fr.

**Keywords:**

Hematological cancer; Hematology; Sepsis; Shock; Solid cancer.

**Abbreviations:**

PMSI, Program of Medicalization of Systems of Information; ICU, intensive care unit; ICD-10, International Classification of Diseases, 10th revision; CCAM, Common Classification of Medical Procedures; STROBE, Strengthening the Reporting of Observational Studies in Epidemiology; ATIH, Technical Agency for Information on Hospitalisation; CNIL, National Commission for Data Protection; INCa, National Cancer Institute; FDep, French Deprivation Index; SAPSII, severity acute physiology score II; IQR, interquartile range; SD, standardized difference; HR, hazard ratio; CI, confidence interval. *
Corresponding author.

E-mail address:

marc.leone@ap-hm.fr (M. Leone).
# Abstract

**Background:**

Septic shock and cancer occur routinely in intensive care unit patients. Our aim was to use the French national hospitalization database to overcome the limitations of the small cohorts used in previous studies that examined the 90-day mortality rate of patients with septic shock and either solid or hematological cancers.

**Methods:**

We performed a retrospective cohort study using data from the French national hospitalization database regarding adult patients with septic shock from 2017 to 2018. The primary outcomes were the hospital mortality rate at 90 days in patients with solid cancer and hematological cancer. Secondary outcomes were the risk factors associated with mortality in our cohort. Associations between 90-day mortality and cancer have been estimated by multivariable analysis.

**Results:**

Septic shock was found in 77,888 patients, including 19,329 patients with solid cancer, 6,498 with hematological cancer, and 52,061 noncancer patients. The 90-day mortality rate was 44.3 %, 53.7%, and 59.1% for noncancer patients, solid cancer patients and hematological cancer patients, respectively. An association was found between 90-day mortality and solid cancer (adjusted hazard ratio 1.55 [1.51-1.59]) or hematological cancer (1.59 [1.53-1.65]) as compared with noncancer patients. Risk factors for 90-day mortality included both hematological and solid cancers.

**Conclusions:**

In septic shock patients, solid cancer and hematological cancer were associated with increased 90-day mortality compared with noncancer patients. Future investigations are required to assess the interplay between cancer and septic shock.

**Registration:**

National Commission for Data Protection (CNIL) under number F20220318151239.
# 1. Introduction

Septic shock, the most severe form of sepsis, is defined as an inappropriate host response to infection and results in one or more life-threatening organ dysfunction(s), with a mortality rate of approximately 45% [1]. In a previous cohort study based on a national database, we found that 53,206 (28.4%) of 187,587 patients with septic shock had a history of cancer, while a diagnosis of “tumor” was reported as the cause of intensive care unit (ICU) admission in 5.9% of patients [2]. In a cohort study from the Netherlands, increased mortality was found at one year in cancer patients with an unplanned ICU admission when compared with mortality in noncancer patients [3]. Among patients with cancer, large variabilities in mortality have been reported [4]. One large retrospective study reported hospital mortality rates of 26% and 56% for patients with solid tumors and hematological malignancies, respectively [5]. The Dutch National Intensive Care Evaluation registry found one-year mortality rates of 60.1%, 46.2%, and 28.3% in hematological cancer, solid cancer, and noncancer patients, respectively [3].

Malignancy, and notably metastatic cancer, is an expected risk factor for sepsis for a number of plausible reasons, including immune deficiency due to chemotherapy, radiotherapy, cancer per se, and catabolism, as well as exposure to invasive procedures, such as surgery and diagnostic protocols [6]. Although several observational studies have reported mortality rates of septic patients with solid or hematological cancers, most were conducted in specialized centers and included only small cohorts [7]. In the present study, our aim was to use the French national database to examine the effects of solid cancer and hematological cancer on the outcomes of patients with septic shock requiring admission to the ICU. We used data collected from 77,888 ICU admissions for septic shock over a 2-year period from 2017 to 2018. Our primary goal was to determine the 90-day mortality rate of patients with septic shock in combination with solid cancer, hematological cancer, or noncancer. A secondary objective was to analyze the risk factors for 90-day mortality in the entire cohort.

# 2. Patients and methods

## 2.1. Selection of data

Our cohort was drawn from data from the French National Program of Medicalisation of Systems of Information (PMSI) database, which compiles administrative and medical information (diagnoses and surgical procedures), as described in a previous study [2]. All adult patients (over 18 years old) with septic shock who were admitted to French ICUs between January 1, 2017, and December 31, 2018, were retrospectively included. Briefly, the
PMSI is based on patient discharge diagnosis groups coded according to the International Classification of Diseases, 10th revision (ICD-10). Technical and medical procedures performed throughout the stay are also coded daily according to the Common Classification of Medical Procedures (CCAM).

The PMSI database is used to determine financial resources and is subject to frequent and thorough checks by both its producer and the payer, with possible financial and legal consequences for those who do not provide data or provide inaccurate data. PMSI data are anonymized and can be reused for research purposes. Due to the PMSI's accuracy and comprehensive data collection, no patient was lost to follow-up during the study period. This study followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines, and as it was based on anonymous and retrospective data, it did not require approval from an ethics committee or informed consent from patients. Data extraction was performed by the authorized public health service of the Public Hospitals of Marseille according to the registered study protocol. Access to the national PMSI database was obtained through a usage agreement signed between the Technical Agency for Information on Hospitalisation (ATIH) and the Public Hospitals of Marseille. In accordance with French law, a declaration of compliance with reference methodology 005 (MR005) was registered with the National Commission for Data Protection (CNIL) under number F20220318151239.

## 2.2. Features of patients

Septic shock was identified using two strategies: either directly from a "septic shock" ICD-10 code (r572) or indirectly using a combination of codes corresponding to a severe infection (sepsis or bacteremia) associated with the use of vasopressors, as described elsewhere [2]. Cancer patients were defined based on the algorithm of the National Cancer Institute (INCa) searched in all PMSI hospitalizations in conventional wards, follow-up care and rehabilitation sites, home hospitalizations, and psychiatric wards during the year preceding hospitalization for septic shock, as well as during hospitalization for septic shock. The study was limited to patients aged 18 years or older. By convention, the group of patients with cancer was considered the cancer group, while patients without cancer were the noncancer group and served as controls. To exclude patients with no severity criteria suggesting the overcoming of septic shock, ICU stays were included only if they lasted at least 48 h, except for patients who died within the first 48 h. In our analysis, if a patient was hospitalized multiple times, we only considered the first hospitalization, ensuring that the number of stays corresponds to the number of unique patients.
## 2.3. Data collected

For each ICU stay, the following data were collected: age (raw data), sex, the Charlson score (a comorbidity measurement tool designed to predict one-year mortality and the comorbidities used to calculate it [for the cancer patients, the cancer and metastasis items were deliberately excluded from the calculation]), presence or absence of neutropenia (neutrophil count in the blood < 500 cells/mm3), reason for ICU admission, time to ICU admission (time from hospital admission to ICU admission), mode of admission (through the emergency department or medical or surgical services), severity acute physiology score II (SAPS II), organ failures, site of infection, health care-associated or community-acquired infection, causative germs and antimicrobial resistance profiles, support therapies (cardiopulmonary resuscitation, mechanical ventilation, blood transfusion, renal replacement therapy, type of cancer (solid or hematological), hospital characteristics (university vs. non-university public vs. private), and mode of ICU discharge.

## 2.4. Outcome measures

The primary outcome was all-cause in-hospital mortality assessed at day 90 according to the status of “solid cancer,” “hematological cancer,” or “noncancer.” Secondary outcomes were the identification of risk factors associated with the 90-day mortality rate. 2.5. Statistical analysis Data are presented as mean _ (standard deviation) for parametric distribution data and as median (interquartile range defined as interquartile range (IQR) [25–75]) for non-parametric data. Categorical data are presented as numbers and percentages.

Standardized differences were used to compare “solid cancer,” “hematological cancer,” and “noncancer” patients. An absolute standardized difference (SD) value <0.20 was chosen to indicate a negligible difference in the mean or prevalence of a variable between the groups. The SD helps to understand the magnitude of the differences found, as well as their statistical significance and determines whether the findings are likely to be due to chance [8,9].

The association between each group and outcome was studied using the Kaplan-Meier method and the log-rank statistic to estimate and compare cumulative death rates. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using Cox survival models with a robust variance estimator to account for clustering within matched pairs. Two models were developed. Frailty 1 included the group, age, sex, smoking, alcohol use, overweight or obesity characteristics, as well as the Charlson Comorbidity Index (0, 1–2, >3), SAPS II (modified, without age), organ failures, ICU supportive therapies, site of
infection, source of hospital admission, time between hospital admission and ICU admission, and hospital characteristics. Frailty 2 included the 17 Charlson comorbidities instead of the Charlson Comorbidity Index.

The proportional-hazards assumption for the Cox models was investigated and confirmed graphically through survival functions over time. A p-value <0.05 was considered statistically significant. Data management and analyses were performed using SAS software. Cox regression analyses were performed using the PROC PHREG statement in SAS.

# 3. Results

## 3.1. Patient features

Among the 77,888 ICU admissions for septic shock from 2017 to 2018, 19,329 patients had solid cancer, 6,498 had hematological cancer, and 52,061 had noncancer affections (Fig. 1).

<figure><img src="image_2.png" /><figcaption>Fig. 1. Flowchart for the patients admitted to the intensive care unit (ICU) with septic shock during the study period 2017–2018.</figcaption></figure>

Almost all differences between patients with solid cancers, patients with hematological cancers, and noncancer patients reached a significant level (Table 1). The SAPS II at ICU admission was higher in patients with hematological cancers than in patients with solid cancers and noncancer patients (Table 1).

Among the 67.4% [95% CI, 67.1–67.8] patients with a positive culture identification, Enterobacter spp. (34.3% [95% CI, 33.9–34.6]), Staphylococcus spp. (23.5% [95% CI, 23.2–23.8]), Streptococcus spp. (21.8% [95% CI, 21.5–22.0]), Pseudomonas aeruginosa (13.3% [95% CI, 13.1–13.6]), and Candida spp. (12.1% [95% CI, 11.9–12.3]) were the most
frequently isolated (Supplemental Table S2). Regarding the sites of infection, the abdominal site was identified in 27.2% [95% CI, 26.6–27.8] of the patients with solid cancers, compared with 12.2% [95% CI, 11.5–13.0] of the patients with hematological cancers and 16.2% [95% CI, 15.9–16.5] of the noncancer patients. The rates of positive culture and the numbers of multidrug-resistant bacteria were similar in the three groups (Table 1). The use of invasive mechanical ventilation was greater in the noncancer patients (80.3% [95% CI, 80.0–80.6]) than in the patients with solid cancers (75.3% [95% CI, 74.7–75.9]) or hematological cancers (71.8% [95% CI, 70.7–72.9]) (Supplemental Table S1).

<table><caption>**Table 1**
Sociodemographic, clinical, and hospital characteristics of the different patient groups.</caption><thead><tr><th rowspan="2">N</th><th rowspan="2">All</th><th rowspan="2">Patients with solid cancer (A)</th><th rowspan="2">Patients with hematologic cancer (B)</th><th rowspan="2">Patients without cancer (C)</th><th colspan="3">A vs. C B vs. C A vs. B</th></tr><tr><th>p-value<sup>a</sup></th><th>p-value<sup>b</sup></th><th>p-value</th></tr></thead><tbody><tr><td>Age: year Mean ± SD [95% CI]</td><td>67.1 ± 14.2 [67.0–67.2]</td><td>68.7 ± 11.3 [68.6–68.9]</td><td>67.4 ± 13.5 [67.1–67.7]</td><td>66.4 ± 15.2 [66.3–66.5]</td><td>&lt;0.001</td><td>&lt;0.001</td><td></td></tr><tr><td>Sex (women): n (%) [95% CI]</td><td>27,939 (35.9%) [35.5–36.1]</td><td>5,997 (31.0%) [30.4–31.7]</td><td>2,204 (33.9%) [32.8–35.1]</td><td>19,738 (37.9%) [37.5–38.3]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Overweight or obese: n (%) [95% CI]</td><td>14,289 (18.3%) [18.1–18.6]</td><td>3,147 (16.3%) [15.8–16.8]</td><td>939 (14.5%) [13.6–15.3]</td><td>10,203 (19.6%) [19.3–19.9]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Smoking addiction: n (%) [95% CI]</td><td>12,529 (16.1%) [15.8–16.3]</td><td>3,572 (18.5%) [17.9–19.0]</td><td>735 (11.3%) [10.5–12.1]</td><td>8,222 (15.8%) [15.5–16.1]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Alcohol addiction: n (%) [95% CI]</td><td>11,408 (14.6%) [14.4–14.9]</td><td>2,552 (13.2%) [12.7–13.7]</td><td>449 (6.9%) [6.3–7.5]</td><td>8,407 (16.1%) [15.8–16.5]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Charlson index: n (%) [95% CI]</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0</td><td>16,365 (21.0%) [20.7–21.3]</td><td>5,001 (25.9%) [25.2–26.5]</td><td>1,561 (24.0%) [23.0–25.1]</td><td>9,803 (18.8%) [18.5–19.2]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>0.003</td></tr><tr><td>1-2</td><td>27,900 (35.8%) [35.5–36.1]</td><td>7,111 (36.8%) [36.1–37.5]</td><td>2,270 (34.9%) [33.8–36.1]</td><td>18,519 (35.6%) [35.2–36.0]</td><td>0.002</td><td>0.310</td><td>0.007</td></tr><tr><td>≥3</td><td>33,623 (43.2%) [42.8–43.5]</td><td>7,217 (37.3%) [36.6–38.0]</td><td>2,667 (41.0%) [39.8–42.2]</td><td>23,739 (45.6%) [45.2–46.0]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>SAPS II score at ICU admission (without age), Mean ± SD [95% CI]</td><td>43.4 ± 23.1 [43.2–43.6]</td><td>43.0 ± 23.5 [42.7–43.3]</td><td>47.7 ± 24.6 [47.1–48.3]</td><td>43.0 ± 22.6 [42.8–43.2]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>SAPS II score at ICU admission (without age, solid and hematologic cancer), Mean ± SD [95% CI]</td><td>40.3 ± 23.3 [40.2–40.5]</td><td>34.0 ± 23.5 [33.7–34.3]</td><td>37.7 ± 24.6 [37.1–38.3]</td><td>43.0 ± 22.6 [42.8–43.2]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Neutropenia</td><td>1,483 (1.90)</td><td>483 (2.50)</td><td>528 (8.13)</td><td>472 (0.91)</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Site of infection: n (%) [95% CI]</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Respiratory</td><td>29,358 (37.7%) [37.3–38.0]</td><td>6,400 (33.1%) [32.4–33.8]</td><td>2,401 (36.9%) [35.8–38.1]</td><td>20,557 (39.5%) [39.1–39.9]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Abdominal</td><td>14,499 (18.6%) [18.3–18.9]</td><td>5,260 (27.2%) [26.6–27.8]</td><td>796 (12.2%) [11.5–13.0]</td><td>8,443 (16.2%) [15.9–16.5]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Urinary tract</td><td>7,319 (9.4%) [9.2–9.6]</td><td>1,818 (9.4%) [9.0–9.8]</td><td>572 (8.8%) [8.1–9.5]</td><td>4,929 (9.5%) [9.2–9.7]</td><td>0.800</td><td>0.083</td><td>0.146</td></tr><tr><td>Cardiac</td><td>7,932 (10.2%) [10.0–10.4]</td><td>1,841 (9.5%) [9.1–9.9]</td><td>841 (12.9%) [12.1–13.8]</td><td>5,250 (10.1%) [9.8–10.3]</td><td>0.026</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Soft tissue</td><td>5,468 (7.0%) [6.8–7.2]</td><td>1,291 (6.7%) [6.3–7.0]</td><td>459 (7.1%) [6.4–7.7]</td><td>3,718 (7.1%) [6.9–7.4]</td><td>0.032</td><td>0.818</td><td>0.285</td></tr><tr><td>Positive culture with identification, n (%) [95% CI]</td><td>52,533 (67.4%) [67.1–67.8]</td><td>13,048 (67.5%) [66.8–68.2]</td><td>4,411 (67.9%) [66.7–69.0]</td><td>35,074 (67.4%) [67.0–67.8]</td><td>0.734</td><td>0.406</td><td>0.573</td></tr><tr><td>Multidrug resistant bacteria, n (%) [95% CI]</td><td>13,777 (17.7%) [17.4–17.9]</td><td>3,527 (18.2%) [17.7–18.8]</td><td>1,218 (18.7%) [17.8–19.7]</td><td>9,032 (17.3%) [17.0–17.7]</td><td>0.005</td><td>0.005</td><td>0.370</td></tr><tr><td>Hospital-acquired infection, n (%) [95% CI]</td><td>21,508 (27.6%) [27.3–27.9]</td><td>6,560 (33.9%) [33.3–34.6]</td><td>1,755 (27.0%) [25.9–28.1]</td><td>13,193 (25.3%) [25.0–25.7]</td><td>&lt;0.001</td><td>0.003</td><td>&lt;0.001</td></tr><tr><td>Source of hospital admission: n (%) [95% CI]</td><td></td><td></td><td></td><td></td><td>0.747</td><td>0.945</td><td>0.801</td></tr><tr><td>Home</td><td>74,842 (96.1%) [95.9–96.2]</td><td>18,851 (96.1%) [95.9–96.4]</td><td>6,242 (96.1%) [95.6–96.5]</td><td>50,019 (96.1%) [95.9–96.2]</td><td>0.747</td><td>0.945</td><td>0.801</td></tr><tr><td>Transfer from other hospital</td><td>3,046 (3.9%) [3.8–4.0]</td><td>748 (3.9%) [3.6–4.1]</td><td>256 (3.9%) [3.5–4.4]</td><td>2,042 (3.9%) [3.8–4.1]</td><td>0.747</td><td>0.945</td><td>0.801</td></tr><tr><td>Time to ICU admission ≤1 day: n (%) [95% CI]</td><td>46,297 (59.4%) [59.1–59.8]</td><td>9,392 (48.6%) [47.9–49.3]</td><td>2,994 (46.1%) [44.9–47.3]</td><td>33,911 (65.1%) [64.7–65.5]</td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr></tbody></table>

SD=0.101 was chosen to indicate a negligible difference in the mean or prevalence of a variable between groups. SD=[0.10] shown in bold. 95% CI: 95% confidence interval.

ICU: Intensive Care Unit.

SAPS II: Simplified Acute Physiology Score.

<sup>a</sup> Standardized difference and p-value between patients with solid cancer and without cancer.

<sup>b</sup> Standardized difference and p-value between patients with hematologic cancer and without cancer.

<sup>c</sup> Standardized difference and p-value between patients with solid and hematologic cancer.

## 3.2. Primary outcome

The in-hospital mortality rates at day 90 were 53.7%, 59.1%, and 44.3% for the patients with solid cancers, patients with hematological cancers, and noncancer patients, respectively (p < 0.05) (Fig. 2). The patients with solid cancers (adjusted HR 1.55 [95% CI, 1.51–1.59]) and hematological cancers (adjusted HR 1.59 [95% CI, 1.53–1.65]) had an increased risk of 90-day mortality compared with the noncancer patients (Table 2). This difference was confirmed using two different statistical models (Frailty 1 and Frailty 2).
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Kaplan-Meier estimates of overall survival at 90 days after intensive care unit (ICU) admission with septic shock.

Color legend:
Green: patients without cancer;
Red: solid cancer patients;
Blue: hematological cancer patients.</figcaption></figure>

<table><caption>**Table 2**
90-day mortality in septic shock patients.</caption><thead><tr><th rowspan="3"></th><th rowspan="3">Alive (N = 40,606)</th><th rowspan="3">Dead (N = 37,282)</th><th rowspan="3">Crude HR Random effect: Finesse [95% CI]</th><th rowspan="3">p-value</th><th colspan="2">Frailty model 1 Random effect: Finesse</th><th colspan="2">Frailty model 2 Random effect: Finesse</th></tr><tr><th colspan="2">Adjusted HR (95% CI)</th><th colspan="2">Adjusted HR (95% CI)</th></tr><tr><th></th><th>p-value</th><th></th><th>p-value</th></tr></thead><tbody><tr><td>Group of patients</td><td></td><td></td><td></td><td>&lt;0.001</td><td></td><td>&lt;0.001</td><td></td><td>&lt;0.001</td></tr><tr><td>Patients without cancer: n (%)</td><td>29,007 (71.4%)</td><td>23,054 (61.8%)</td><td>1</td><td></td><td>1</td><td></td><td>1</td><td></td></tr><tr><td>Patients with solid cancer: n (%)</td><td>8,943 (22.0%)</td><td>10,386 (27.9%)</td><td>1.26 [1.24-1.29]</td><td></td><td>1.55 [1.51-1.59]</td><td></td><td>1.55 [1.51-1.59]</td><td></td></tr><tr><td>Patients with Hematologic cancer: n (%)</td><td>2,656 (6.5%)</td><td>3,842 (10.3%)</td><td>1.49 [1.44-1.54]</td><td></td><td>1.59 [1.53-1.65]</td><td></td><td>1.60 [1.55-1.66]</td><td></td></tr></tbody></table>

95% CI: 95% confidence interval.
HR: Hazard Ratio.

### 3.3. Risk factors associated with 90-day mortality

Poor outcomes were associated with admission to the ICU with cancer, the type of cancer (solid vs. hematological), advanced age, increased severity score, each organ failure, the ICU supportive therapies except blood transfusion, and admission to a non-university public hospital (as compared with other public hospitals). In contrast, overweight, Charlson Comorbidity Index 1 - 2, a known source of infection, cardiovascular failure, hospital-acquired infection, direct admission from home to the ICU, and time to ICU admission of less than 24 h were identified as protective factors.
## 4. Discussion

Patients with solid cancers represented approximately 25% of our cohort of patients with septic shock, while those with hematological cancer represented approximately 8% of these patients. The 90-day mortality rate was higher in the cancer patients than in the noncancer patients. Among the cancer patients, those with hematological cancers were at a higher risk of 90-day mortality than those with solid cancers. Our results also suggested an association between 90-day mortality and microbial source identification, as well as 90-day mortality and the isolation of the pathogen responsible for the infection. Early admission to the ICU (i.e., within the first 24 h after diagnosis) was also associated with improved outcomes. Using a French national database, these findings confirmed previous studies assessing the outcomes of cancer patients in the ICU [3,5]. As reported in these studies, despite efforts to enhance survival, septic shock in patients with hematologic malignancies is still associated with high mortality rates and poor 90-day survival. These results suggest the need for an urgent call to action with higher awareness, including the further evaluation of interventions such as earlier ICU admission, aminoglycosides administration, and G-CSF treatment [10–12].

By day 90, approximately 40% of our patients with hematological cancer had survived. To reflect the interplay between septic shock and cancer, we deliberately chose an early assessment since the long-term outcome could reflect the underlying disease rather than septic shock. However, van der Zee et al. found a one-year mortality rate of 60% in patients with unplanned ICU admissions in the Netherlands [3]. The interest of our paper was to focus on a large number of patients with septic shock and to underline, in these patients, that early interventions may be associated with improved outcomes, while most previous studies assessed the outcomes of a global population of ICU patients. Thus, our findings may respond to the concerns of clinicians at the bedside.

We identified risk factors that were already reported but our large-scale study provides a strong validation of these factors. In particular, our use of the French database confirmed being old, having comorbidities, developing several organ failures, and receiving supportive therapies were associated with poor outcomes. The large number of patients included in our study increased the validity of our findings. We also found an association between being admitted to university hospitals vs. being admitted to public non-university hospitals. This could reflect an increased volume, as suggested in a previous study [10].

Early ICU admission, identification of the source of infection, and isolation of pathogens responsible for infection were all associated with improved outcomes in our large cohort. Importantly, these findings validated the findings of other cohort studies at a large scale [11–
13]. Indeed, an observational study that included 1,611 immunocompromised patients with acute hypox-emic respiratory failure found that failure to identify the etiology of acute respiratory failure was associated with higher mortality rates [7]. Early ICU admission has been repeatedly associated with improved outcomes in small cohorts of patients with cancer [7]. This improvement may be explained by the administration of antibiotics within the first hours of sepsis [14] or by earlier source control due to the removal of an indwelling catheter [15].

The main strength of our study is that it used an extremely large national database that included an enormous number of patients with vast amounts and types of data. To our knowledge, this is the largest study in this field. However, several limitations must be acknowledged. First, our results derived from a large database could have limitations due to coding procedures. Second, the causes of mortality and, notably, the withdrawal or withholding of life-sustaining treatments were not determined. Third, previous comparable studies included unplanned ICU admissions of patients with cancer, but this type of information was not available in our database. Fourth, as we have provided crude data, confounding factors may have had an undetermined influence on our results. Fifth, as the national database does not include serum lactate, our study did not use the Sepsis-3 criteria to identify patients in septic shock. Thus, we included patients with a sepsis code and vasopressor use code to avoid under triage. Finally, our database analysis was based on the 2017–2018 period, but no significant changes have been expected since this period as underlined by recent papers underlining the urgent persistently high mortality in cancer patients with sepsis [10–12].

In conclusion, our analysis of 77,888 ICU patients with septic shock found that the 90-day mortality rate was higher in patients with hematological cancers than in those with solid cancers. In addition, the 90-day mortality rate was higher for patients with either cancer type than for noncancer patients. Previous studies had included only small cohorts of septic patients with cancer, notably regarding the potential benefit of early admission to the ICU for those patients and the need to identify the source of their infections. Our study confirmed each of these previous findings on a nationwide database, the dimension of this database reinforcing the validity of each result. Due to the high global number of patients with cancer who experience septic shock, future investigations should more broadly assess the interplay between these two conditions.

CRediT authorship contribution statement

Conception and design: Marc Leone, Ines Lakbar, and Laurent Boyer.

Collection and assembly of data: Antoine Bianchi, Guillaume Fond, Gary Duclos, and Laurent Zieleskiewicz.
Data analysis and interpretation: Antoine Bianchi, Yann Brousse, Ines Lakbar, Vanessa Pauly, Veronica Orleans, Laurent Boyer, and Marc Leone.

Manuscript writing:

All authors.

Final approval of manuscript:

All authors.

Accountable for all aspects of the work:

All authors.

## Funding

This work did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.

## Declaration of competing interest

Marc Leone reports a relationship with AOP Orphan Pharma-ceuticals GmbH that includes: consulting or advisory. Marc Leone reports a relationship with Viatris that includes: consulting or advisory. Marc Leone reports a relationship with Previa that includes: consulting or advisory. Marc Leone reports a relationship with Edwards Lifesciences Corporation that includes: speaking and lecture fees. Marc Leone reports a relationship with Shionogi and Co Ltd that includes: speaking and lecture fees. Marc Leone reports a relationship with Grifols Inc that includes: speaking and lecture fees. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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