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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\n ICU<\/jats:styled-content>\n for sepsis were extracted from the databases\n MIMIC<\/jats:styled-content>\n \u2010\n IV<\/jats:styled-content>\n and\n eICU<\/jats:styled-content>\n \u2010\n CRD<\/jats:styled-content>\n . Using Extreme Gradient Boosting, we estimated the odds for invasive mechanical ventilation (\n IMV<\/jats:styled-content>\n ) or vasopressors. Targeted maximum likelihood estimation (\n TMLE<\/jats:styled-content>\n ) models estimated treatment effects of\n IMV<\/jats:styled-content>\n and vasopressors on in\u2010hospital mortality and 28 hospital\u2010free days. 58,988 adult septic patients were included, of which 6145 had cancer. In\u2010hospital mortality was higher for cancer patients (30.3% vs. 16.1%). Patients with cancer had lower odds of receiving\n IMV<\/jats:styled-content>\n (\n aOR<\/jats:styled-content>\n [95%\n CI<\/jats:styled-content>\n ], 0.94 [0.90\u20130.97]); pronounced for hematologic patients (\n aOR<\/jats:styled-content>\n 0.89 [0.84\u20130.93]). Odds for vasopressors were also lower for hematologic patients (\n aOR<\/jats:styled-content>\n 0.89 [0.84\u20130.94]).\n TMLE<\/jats:styled-content>\n models found\n IMV<\/jats:styled-content>\n to be overall associated with higher in\u2010hospital mortality for solid and hematological patients (\n ATE<\/jats:styled-content>\n 3% [1%\u20135%], 6% [3%\u20139%], respectively), while vasopressors were associated with higher in\u2010hospital mortality for patients with solid and metastatic cancer (\n ATE<\/jats:styled-content>\n 6% [4%\u20138%], 3% [1%\u20136%], respectively). We utilized\n US<\/jats:styled-content>\n \u2010wide\n ICU<\/jats:styled-content>\n data to estimate a relationship between mortality and the use of common therapies. With the exception of hematologic patients being less likely to receive\n IMV<\/jats:styled-content>\n , 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.\n <\/jats:p>","DOI":"10.1002\/ijc.70138","type":"journal-article","created":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T14:07:57Z","timestamp":1757340477000},"page":"707-715","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A causal inference framework to compare the effectiveness of life\u2010sustaining\n ICU<\/scp>\n therapies\u2014using the example of cancer patients with sepsis"],"prefix":"10.1002","volume":"158","author":[{"given":"Jo\u00e3o","family":"Matos","sequence":"first","affiliation":[{"name":"Faculty of Engineering University of Porto Porto Portugal"},{"name":"Laboratory for Computational Physiology, Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0199-0184","authenticated-orcid":false,"given":"Tristan","family":"Struja","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge Massachusetts USA"},{"name":"Medical University Clinic Kantonsspital Aarau Aarau Switzerland"},{"name":"Clinic of Internal Medicine Spital Muri Muri Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naira Link","family":"Woite","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Restrepo","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge Massachusetts USA"},{"name":"Telematics Department University of Cauca Popayan Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andre Kurepa","family":"Waschka","sequence":"additional","affiliation":[{"name":"College of Liberal Arts and Sciences Mercer University Macon Georgia USA"},{"name":"Mathematics & Statistics Elon University Elon North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leo A.","family":"Celi","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher M.","family":"Sauer","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, Institute for Medical Engineering and Science 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