title: Time-Limited Trials of Intensive Care for Critically Ill Patients With Cancer: How Long Is Long Enough?
abstract: OBJECTIVE
  Time-limited trials of intensive care are commonly used in patients perceived to have a poor prognosis. The optimal duration of such trials is unknown. Factors such as a cancer diagnosis are associated with clinician pessimism and may affect the decision to limit care independent of a patient's severity of illness.
  
  
  OBJECTIVE
  To identify the optimal duration of intensive care for short-term mortality in critically ill patients with cancer.
  
  
  METHODS
  Decision analysis using a state-transition microsimulation model was performed to simulate the hospital course of patients with poor-prognosis primary tumors, metastatic disease, or hematologic malignant neoplasms admitted to medical and surgical intensive care units. Transition probabilities were derived from 920 participants stratified by sequential organ failure assessment (SOFA) scores to identify severity of illness. The model was validated in 3 independent cohorts with 349, 158, and 117 participants from quaternary care academic hospitals. Monte Carlo microsimulation was performed, followed by probabilistic sensitivity analysis. Outcomes were assessed in the overall cohort and in solid tumors alone.
  
  
  METHODS
  Time-unlimited vs time-limited trials of intensive care.
  
  
  METHODS
  30-day all-cause mortality and mean survival duration.
  
  
  RESULTS
  The SOFA scores at ICU admission were significantly associated with mortality. A 3-, 8-, or 15-day trial of intensive care resulted in decreased mean 30-day survival vs aggressive care in all but the sickest patients (SOFA score, 5-9: 48.4% [95% CI, 48.0%-48.8%], 60.6% [95% CI, 60.2%-61.1%], and 66.8% [95% CI, 66.4%-67.2%], respectively, vs 74.6% [95% CI, 74.3%-75.0%] with time-unlimited aggressive care; SOFA score, 10-14: 36.2% [95% CI, 35.8%-36.6%], 44.1% [95% CI, 43.6%-44.5%], and 46.1% [95% CI, 45.6%-46.5%], respectively, vs 48.4% [95% CI, 48.0%-48.8%] with aggressive care; SOFA score, ≥ 15: 5.8% [95% CI, 5.6%-6.0%], 8.1% [95% CI, 7.9%-8.3%], and 8.3% [95% CI, 8.1%-8.6%], respectively, vs 8.8% [95% CI, 8.5%-9.0%] with aggressive care). However, the clinical magnitude of these differences was variable. Trial durations of 8 days in the sickest patients offered mean survival duration that was no more than 1 day different from time-unlimited care, whereas trial durations of 10 to 12 days were required in healthier patients. For the subset of patients with solid tumors, trial durations of 1 to 4 days offered mean survival that was not statistically significantly different from time-unlimited care.
  
  
  CONCLUSIONS
  Trials of ICU care lasting 1 to 4 days may be sufficient in patients with poor-prognosis solid tumors, whereas patients with hematologic malignant neoplasms or less severe illness seem to benefit from longer trials of intensive care.
authors.affiliation: Program in Global Surgery and Social Change, Harvard Medical School, Boston, Massachusetts 2Department of Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts.
authors.forename: Mark G
authors.initials: MG
authors.lastname: Shrime
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands 4Department of Population Health Science and Policy, Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York.
authors.forename: Bart S
authors.initials: BS
authors.lastname: Ferket
authors.affiliation: Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Boston, Massachusetts.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Scott
authors.affiliation: School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada.
authors.forename: Joon
authors.initials: J
authors.lastname: Lee
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts8Harvard Medical School, Boston, Massachusetts.
authors.forename: Diana
authors.initials: D
authors.lastname: Barragan-Bradford
authors.affiliation: Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Boston, Massachusetts.
authors.forename: Tom
authors.initials: T
authors.lastname: Pollard
authors.affiliation: Intensive Care Department, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia10King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.
authors.forename: Yaseen M
authors.initials: YM
authors.lastname: Arabi
authors.affiliation: Intensive Care Department, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia10King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.
authors.forename: Hasan M
authors.initials: HM
authors.lastname: Al-Dorzi
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts8Harvard Medical School, Boston, Massachusetts.
authors.forename: Rebecca M
authors.initials: RM
authors.lastname: Baron
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands 11Center for Health Decision Science, Harvard School of Public Health, Boston, Massachusetts.
authors.forename: M G Myriam
authors.initials: MG
authors.lastname: Hunink
authors.affiliation: Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Boston, Massachusetts8Harvard Medical School, Boston, Massachusetts.
authors.forename: Leo A
authors.initials: LA
authors.lastname: Celi
authors.affiliation: Harvard Medical School, Boston, Massachusetts12Pulmonary and Critical Care Unit, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Peggy S
authors.initials: PS
authors.lastname: Lai
mesh_terms: D000046:Academic Medical Centers; D000368:Aged; D000369:Aged, 80 and over; D001900:Boston; D003198:Computer Simulation; D003422:Critical Care; D016638:Critical Illness; D016208:Databases, Factual; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009010:Monte Carlo Method; D009369:Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000628:therapy*; D063305:Organ Dysfunction Scores; D018579:Patient Selection; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome