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A causal inference framework to compare the effectiveness of life-sustaining ICU therapies—using the example of cancer patients with sepsis

Author(s)
Matos, João; Struja, Tristan; Woite, Naira Link; Restrepo, David; Waschka, Andre Kurepa; Celi, Leo A; Sauer, Christopher M; ... Show more Show less
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Abstract
The rise in cancer patients could lead to an increase in intensive care units (ICUs) admissions. We explored differences in treatment practices and outcomes of invasive therapies between patients with sepsis with and without cancer. Adults from 2008 to 2019 admitted to the ICU for sepsis were extracted from the databases MIMIC-IV and eICU-CRD. Using Extreme Gradient Boosting, we estimated the odds for invasive mechanical ventilation (IMV) or vasopressors. Targeted maximum likelihood estimation (TMLE) models estimated treatment effects of IMV and vasopressors on in-hospital mortality and 28 hospital-free days. 58,988 adult septic patients were included, of which 6145 had cancer. In-hospital mortality was higher for cancer patients (30.3% vs. 16.1%). Patients with cancer had lower odds of receiving IMV (aOR [95%CI], 0.94 [0.90–0.97]); pronounced for hematologic patients (aOR 0.89 [0.84–0.93]). Odds for vasopressors were also lower for hematologic patients (aOR 0.89 [0.84–0.94]). TMLE models found IMV to be overall associated with higher in-hospital mortality for solid and hematological patients (ATE 3% [1%–5%], 6% [3%–9%], respectively), while vasopressors were associated with higher in-hospital mortality for patients with solid and metastatic cancer (ATE 6% [4%–8%], 3% [1%–6%], respectively). We utilized US-wide ICU data to estimate a relationship between mortality and the use of common therapies. With the exception of hematologic patients being less likely to receive IMV, we did not find differential treatment patterns. We did not demonstrate an average survival benefit for therapies, underscoring the need for a more granular analysis to identify subgroups who benefit from these interventions.
Date issued
2025-09-08
URI
https://hdl.handle.net/1721.1/163611
Department
Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology; Institute for Medical Engineering and Science
Journal
International Journal of Cancer
Publisher
Wiley
Citation
Matos J, Struja T, Woite NL, et al. A causal inference framework to compare the effectiveness of life-sustaining ICU therapies—using the example of cancer patients with sepsis. Int J Cancer. 2025; 1-9.
Version: Final published version

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