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dc.contributor.authorMatos, João
dc.contributor.authorStruja, Tristan
dc.contributor.authorWoite, Naira Link
dc.contributor.authorRestrepo, David
dc.contributor.authorWaschka, Andre Kurepa
dc.contributor.authorCeli, Leo A
dc.contributor.authorSauer, Christopher M
dc.date.accessioned2025-11-10T16:41:23Z
dc.date.available2025-11-10T16:41:23Z
dc.date.issued2025-09-08
dc.identifier.urihttps://hdl.handle.net/1721.1/163611
dc.description.abstractThe 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.en_US
dc.language.isoen
dc.publisherWileyen_US
dc.relation.isversionofhttps://doi.org/10.1002/ijc.70138en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceWileyen_US
dc.titleA causal inference framework to compare the effectiveness of life-sustaining ICU therapies—using the example of cancer patients with sepsisen_US
dc.typeArticleen_US
dc.identifier.citationMatos 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.en_US
dc.contributor.departmentHarvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiologyen_US
dc.contributor.departmentInstitute for Medical Engineering and Scienceen_US
dc.relation.journalInternational Journal of Canceren_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2025-11-10T16:10:29Z
dspace.orderedauthorsMatos, J; Struja, T; Woite, NL; Restrepo, D; Waschka, AK; Celi, LA; Sauer, CMen_US
dspace.date.submission2025-11-10T16:10:30Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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