Multicenter outcome study of cancer patients admitted to the intensive care unit: a probability of mortality model.

Abstract

We report a disease-specific multivariable logistic regression model to estimate the probability of hospital mortality in a cohort of critically ill cancer patients admitted to the ICU. The model consists of 16 unambiguous and readily available variables. This model should move the discussion regarding appropriate use of ICU resources forward. Additional validation in a community hospital setting is warranted.

General Prognostic Scores in Outcome Prediction for Cancer Patients Admitted to the Intensive Care Unit

“…To the best of our knowledge, our finding that scores on APACHE II, SOFA, and SAPS II and 3 additional models are all acceptable prognostic indicators in the same cohort of cancer patients has not been previously reported. However, in a similar study 29 of 5 general severity-of-illness scores (APACHE II and III-J, SAPS II, Mortality Probability Model 37 at ICU admission and 24 hours later), and 1 specific score, the ICU Cancer Mortality Model (ICM), 38 discrimination was good for all 6 of the studied models, but calibration was uniformly insufficient. Of note, a well-known weakness of the HosmerLemeshow goodness-of-fit tests is that the sample size has a major effect on the measured calibration but does not affect discrimination.…”

Septic shock and multiple organ failure after hematopoietic stem cell transplantation: treatment with recombinant human activated protein C

“…However, using the mortality probability model II (MPM II) 13 developed for critically ill cancer patients admitted to the ICU, the estimated mortality rate for this patient was 92%.…”

Outcome in critically ill cancer patients: past and present

“…Age has only a minimal impact on the six-month survival in critically cancer patients 48 . The performance status and comorbidity are much more important 44,49,50 for both the long-term and the short-term survival. The short-term survival, however, will essentially depend upon the number and severity of organ failures and the subsequent need for advanced life-supporting measures such as mechanical ventilation and/or renal replacement therapy on the one hand 16,[28][29][30][31][32][33][34][35] , and the reversibility of the organ failure on the other 17,51 .…”

“…However, the decision to provide or withhold advance life-supporting therapy remains difficult in an individual patient in daily practice. The complexity of such a decision cannot be replaced by a simple number of prognostic indicators, by a rule of thumb or even by a more complex scoring system 44,45 . Even ICU physicians often dealing with such patients fail to discriminate well between survivors and non-survivors 46 .…”

“…Even ICU physicians often dealing with such patients fail to discriminate well between survivors and non-survivors 46 . Nevertheless, a number of prognostic indicators have been identified to guide physicians in their decisionmaking 15,16,[27][28][29][30][31]44 . Of course beside these prognostic indicators, the patient's perceived quality of life and the wishes of the patient and/or the relatives should also be taken into account.…”