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Critical illness in patients with hematologic malignancy: a population-based cohort study

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An Editorial to this article was published on 14 September 2021

Abstract

Purpose

To describe the modern incidence and predictors of ICU admission for adult patients newly diagnosed with a hematologic malignancy.

Methods

We conducted a population-based cohort study of adults with a new diagnosis of hematologic malignancy (April 1, 2006–March 31, 2017) in Ontario, Canada. We described the baseline demographic, clinical and laboratory predictors of ICU admission and subsequent mortality. The primary outcome was the incidence of ICU admission within 1 year of hematologic malignancy diagnosis. We assessed the predictors of ICU admission using Cox-proportional models that accounted for the competing risk of death and reported as subdistribution hazard ratios (sHR) with 95% confidence intervals (CI).

Results

A total of 87,965 patients (mean [SD] age, 67.8 (15.7) years) were included. The 1-year incidence of ICU admission was 13.9% (median time 35 days), ranging from 7.3% (indolent lymphoma) to 22.5% (acute myeloid leukemia). After multivariable adjustment, compared to indolent lymphoma, acute myeloid leukemia (sHR, 3.09; 95% CI 2.84–3.35), aggressive non-Hodgkin lymphoma (sHR, 2.47; 95% CI 2.31–2.65) and acute lymphoblastic leukemia (sHR, 2.46; 95% CI 2.15–2.80) had the highest risk of ICU admission. Comorbidities such as cardiovascular disease (sHR, 2.09; 95% CI 2.01–2.19), chronic obstructive pulmonary disease (sHR, 1.33; 95% CI 1.26–1.39) and baseline laboratory abnormalities (anemia, thrombocytopenia and high creatinine) were also associated with ICU admission. Among ICU patients, 36.7% required invasive mechanical ventilation and in-hospital mortality was 31%.

Conclusion

Critical illness in patients with a newly diagnosed hematologic malignancy is frequent, occurring early after diagnosis. Certain baseline characteristics can help identify those patients at the highest risk.

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Data availability

The study was conducted using relevant provincial administrative databases available at ICES in Toronto, Canada. This data is not publicly available and only researchers with ICES credentials can access this data.

Code availability

The codes used for this study will be available upon reasonable request to the corresponding author.

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Acknowledgements

This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC). Parts of this material are based on data and information compiled and provided by Cancer Care Ontario (CCO). The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred. The authors would also like to thank Dr. Fernando Binder for his help with Fig. 4.

Funding

BF was supported by a Vanier Canada Graduate Scholarship. DS holds operating grants from the Canadian Institute for Health Research. HW is supported by a Canada Research Chair [Tier 2] in Critical Care Organization and Outcomes.

Author information

Authors and Affiliations

  1. Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada

    Bruno L. Ferreyro, Damon C. Scales, Hannah Wunsch & Laveena Munshi

  2. Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

    Bruno L. Ferreyro, Damon C. Scales, Hannah Wunsch & Laveena Munshi

  3. Department of Medicine, Sinai Health System and University Health Network, Toronto, Canada

    Bruno L. Ferreyro & Laveena Munshi

  4. Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, Toronto, Canada

    Damon C. Scales & Hannah Wunsch

  5. ICES, Toronto, ON, Canada

    Damon C. Scales, Hannah Wunsch, Matthew C. Cheung & Refik Saskin

  6. Applied Health Research Center (AHRC), Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada

    Damon C. Scales

  7. Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

    Matthew C. Cheung

  8. Division of Hematology/Medical Oncology, Department of Medicine, University of Toronto, Toronto, Canada

    Matthew C. Cheung, Vikas Gupta & Santhosh Thyagu

  9. Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada

    Vikas Gupta & Santhosh Thyagu

  10. Mount Sinai Hospital, 600 University Avenue, 18-210, Toronto, ON, M5G 1X5, Canada

    Bruno L. Ferreyro

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  1. Bruno L. Ferreyro
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Contributions

BLF had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: BLF, DCS, HW, RS, LM. Acquisition, analysis and interpretation of data: all authors. Drafting of the manuscript: BLF, DCS, LM. Critical revision of the manuscript for important intellectual content and approval of the final draft: all authors. Statistical analysis: BLF, RS.

Corresponding author

Correspondence to Bruno L. Ferreyro.

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ICES is an independent, non-profit research institute whose legal status under Ontario’s health information privacy law allows it to collect and analyze health-care and demographic data, without consent, for health system evaluation and improvement. The use of the data in this project is authorized under section 45 of Ontario’s Personal Health Information Protection Act (PHIPA) and does not require review by a Research Ethics Board.

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Ferreyro, B.L., Scales, D.C., Wunsch, H. et al. Critical illness in patients with hematologic malignancy: a population-based cohort study. Intensive Care Med 47, 1104–1114 (2021). https://doi.org/10.1007/s00134-021-06502-2

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