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Intensive Care Medicine

, Volume 30, Issue 3, pp 430–436 | Cite as

Comparison of three severity scores for critically ill cancer patients

  • Peter Schellongowski
  • Michael Benesch
  • Thomas Lang
  • Friederike Traunmüller
  • Christian Zauner
  • Klaus Laczika
  • Gottfried J. Locker
  • Michael Frass
  • Thomas Staudinger
Original

Abstract

Objective

To compare three scoring systems, the Acute Physiology and Chronic Health Evaluation (APACHE) II, the Simplified Acute Physiology Score (SAPS) II and a modified Mortality Probability Model II (ICU cancer mortality model, ICMM) for their prognostic value for mortality during hospital stay in a group of cancer patients admitted to a medical ICU.

Design

Prospective cohort study.

Setting

Medical ICU of a tertiary care hospital.

Patients

Two hundred forty-two consecutive cancer patients admitted to the ICU.

Measurements and results

Variables included in APACHE II, SAPS II and the ICMM scores as well as demographic data were assessed during the first 24 h of stay in the ICU. Hospital mortality was measured; it was 44%. Calibration for all three scoring systems was acceptable, SAPS II yielded a significantly superior discrimination between survivors and non-survivors. The areas under the receiver operating characteristic curves were 0.776 for APACHE II, 0.825 for SAPS II and 0.698 for the ICMM.

Conclusion

The SAPS II was superior to APACHE II and ICMM. The newly developed ICMM does not improve mortality prediction in critically ill cancer patients.

Keywords

Scoring Cancer Critical care Acute Physiology and Chronic Health Evaluation (APACHE) II Simplified Acute Physiology Score (SAPS) II Mortality Probability Model II 

References

  1. 1.
    Sculier JP, Markiewicz E (1991) Medical cancer patients and intensive care. Anticancer Res 11:2171–2174PubMedGoogle Scholar
  2. 2.
    Baumann WR, Jung RC, Koss M, Boylen CT, Navarro L, Sharma OP (1986) Incidence and mortality of adult respiratory distress syndrome: a prospective analysis from a metropolitan hospital. Crit Care Med 14:1–4PubMedGoogle Scholar
  3. 3.
    Sussman NL, Lake JR (1996) Treatment of hepatic failure 1996: current concepts and progress toward liver dialysis. Am J Kidney Dis 27:605–621PubMedGoogle Scholar
  4. 4.
    Krafft P, Fridrich P, Pernerstorfer T, Fitzgerald RD, Koc D, Schneider B, Hammerle AF, Steltzer H (1996) The acute respiratory distress syndrome: definitions, severity and clinical outcome. An analysis of 101 clinical investigations. Intensive Care Med 22:519–529PubMedGoogle Scholar
  5. 5.
    Marik PE, Craft M (1997) An outcomes analysis of in-hospital cardiopulmonary resuscitation: the futility rationale for do not resuscitate orders. J Crit Care 12:142–146PubMedGoogle Scholar
  6. 6.
    The British Thoracic Society Research Committee and The Public Health Laboratory Service (1992) The aetiology, management and outcome of severe community-acquired pneumonia on the intensive care unit. Respir Med 86:7–13PubMedGoogle Scholar
  7. 7.
    Massion PB, Dive AM, Doyen C, Bulpa P, Jamart J, Bosly A, Installe E (2002) Prognosis of hematologic malignancies does not predict intensive care mortality. Crit Care Med 30:2260–2270PubMedGoogle Scholar
  8. 8.
    Sculier JP, Paesmans M, Markiewicz E, Berghmans T (2000) Scoring systems in cancer patients admitted for an acute complication in a medical intensive care unit. Crit Care Med 28:2786–2792PubMedGoogle Scholar
  9. 9.
    Staudinger T, Stoiser B, Mullner M, Locker GJ, Laczika K, Knapp S, Burgmann H, Wilfing A, Kofler J, Thalhammer F, Frass M (2000) Outcome and prognostic factors in critically ill cancer patients admitted to the intensive care unit. Crit Care Med 28:1322–1328PubMedGoogle Scholar
  10. 10.
    Groeger JS, Lemeshow S, Price K, Nierman DM, White P Jr, Klar J, Granovsky S, Horak D, Kish SK (1998) Multicenter outcome study of cancer patients admitted to the intensive care unit: a probability mortality model. J Clin Oncol 16:761–770PubMedGoogle Scholar
  11. 11.
    Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, Sirio CA, Murphy DJ, Lotring T, Damiano A (1991) The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 100:1619–1636PubMedGoogle Scholar
  12. 12.
    Le Gall JR, Lemeshow S, Saulnier F (1993) A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study. JAMA 270:2957–2964PubMedGoogle Scholar
  13. 13.
    Lemeshow S, Hosmer DW Jr (1982) A review of goodness-of-fit statistics for use in the development of logistic regression models. Am J Epidemiol 115:92–106PubMedGoogle Scholar
  14. 14.
    Weinstein MC, Fineberg HV (1980) Clinical decision analysis. Saunders, PhiladelphiaGoogle Scholar
  15. 15.
    DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845PubMedGoogle Scholar
  16. 16.
    Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39:561–577PubMedGoogle Scholar
  17. 17.
    Rosenberg AL (2002) Recent innovations in intensive care unit risk-prediction models. Curr Opin Crit Care 8:321–330CrossRefPubMedGoogle Scholar
  18. 18.
    Patel PA, Grant BJB (1999) Application of mortality prediction systems to individual intensive care units. Intensive Care Med 25:977–982PubMedGoogle Scholar
  19. 19.
    Carson SS, Bach PB (2001) Predicting mortality in patients suffering from prolonged critical illness: an assessment of four severity-of-illness measures. Chest 120:928–933CrossRefPubMedGoogle Scholar
  20. 20.
    Reina A, Vazquez G, Aguayo E, Bravo I, Colmenero M, Bravo M (1997) Mortality discrimination in acute myocardial infarction: comparison between APACHE III and SAPS II prognosis systems. Intensive Care Med 23:326–330CrossRefPubMedGoogle Scholar
  21. 21.
    Bein T, Frohlich D, Pomsl J, Forst H, Pratschke E (1995) The predictive value of four scoring systems in liver transplant recipients. Intensive Care Med 21:32–37PubMedGoogle Scholar
  22. 22.
    Fiaccadori E, Maggiore U, Lombardi M, Leonardi S, Rotelli C, Borghetti A (2000) Predicting patient outcome from acute renal failure comparing three general severity of illness scoring systems. Kidney Int 58:283–292PubMedGoogle Scholar
  23. 23.
    Guiguet M, Blot F, Escudier B, Antoun S, Leclercq B, Nitenberg G (1998) Severity of illness scores for neutropenic patients in an intensive care unit: which is the best predictor? Do multiple assessment times improve the predictive value? Crit Care Med 26:488–493Google Scholar
  24. 24.
    Kroschinsky F, Weise M, Illmer T, Haenel M, Bornhaeuser M, Hoeffken G, Ehninger G, Schuler U (2002) Outcome and prognostic features of intensive care unit treatment in patients with hematological malignancies. Intensive Care Med 28:1294–1300CrossRefGoogle Scholar
  25. 25.
    Groeger JS, White P, Nierman DM, Glassmann J, Shi W, Horak D, Price K (1999) Outcome of cancer patients requiring mechanical ventilation. J Clin Oncol 17:991–997PubMedGoogle Scholar
  26. 26.
    Lemeshow S, Le Gall JR (1994) Modeling the severity of illness of ICU patients. A systems update. JAMA 272:1049–1055PubMedGoogle Scholar
  27. 27.
    Ferrand E, Robert R, Ingrand P, Lemaire F (2001) Withholding and withdrawal of life support in intensive-care units in France: a prospective survey. Lancet 357:9–14PubMedGoogle Scholar
  28. 28.
    Schapira DV, Studnicki J, Bradham DD, Wolff P, Jarrett A (1993) Intensive care, survival and expense of treating critically ill cancer patients. JAMA 269:783–786PubMedGoogle Scholar
  29. 29.
    Brunet F, Lanore JJ, Dhainaut JF, Dreyfus F, Vaxelaire JF, Nouira S, Giraud T, Armaganidis A, Monsallier JF (1990) Is intensive care justified for patients with haematological malignancies? Intensive Care Med 16:291–297PubMedGoogle Scholar
  30. 30.
    Azoulay E, Moreau D, Alberti C, Leleu G, Adrie C, Barboteu M, Cottu P, Levy V, Le Gall JR, Schlemmer B (2000) Predictors of short-term mortality in critically ill patients with solid malignancies. Intensive Care Med 26:1817–1823CrossRefPubMedGoogle Scholar
  31. 31.
    Faber-Langendoen K, Caplan AL, McGlave PB (1993) Survival of adult bone marrow transplant patients receiving mechanical ventilation: a case for restricted use. Bone Marrow Transplant 12:501–507PubMedGoogle Scholar
  32. 32.
    Crawford SW (1998) Using outcome research to improve the management of blood and marrow transplant recipients in the intensive care unit. New Horiz 6:69–74PubMedGoogle Scholar
  33. 33.
    Khassawneh BY, White P, Anaissie EJ, Barlogie B, Hiller FC (2002) Outcome from mechanical ventilation after autologous peripheral blood stem cell transplantation. Chest 121:185–188CrossRefPubMedGoogle Scholar
  34. 34.
    Epner DE, White P, Krasnoff M, Khanduja S, Kimball KT, Knaus WA (1996) Outcome of mechanical ventilation for adults with hematologic malignancy. J Investig Med 44:254–260PubMedGoogle Scholar
  35. 35.
    Shaw A, Weavind L, Feeley T (2001) Mechanical ventilation in critically ill cancer patients. Curr Opin Oncol 13:224–228CrossRefPubMedGoogle Scholar
  36. 36.
    Kongsgaard UE, Meidell NK (1999) Mechanical ventilation in critically ill cancer patients: outcome and utilisation of resources. Support Care Cancer 7:95–99CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • Peter Schellongowski
    • 1
  • Michael Benesch
    • 2
  • Thomas Lang
    • 2
  • Friederike Traunmüller
    • 1
  • Christian Zauner
    • 3
  • Klaus Laczika
    • 1
  • Gottfried J. Locker
    • 1
  • Michael Frass
    • 1
  • Thomas Staudinger
    • 1
  1. 1.Department of Internal Medicine IUniversity of ViennaViennaAustria
  2. 2.Institute for Medical StatisticsUniversity of ViennaViennaAustria
  3. 3.Department of Internal Medicine IVUniversity of ViennaViennaAustria

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