Advertisement

Supportive Care in Cancer

, Volume 22, Issue 3, pp 611–617 | Cite as

Comparative multidisciplinary prediction of survival in patients with advanced cancer

  • A FairchildEmail author
  • B Debenham
  • B Danielson
  • F Huang
  • S Ghosh
Original Article

Abstract

Purpose

The expected survival of patients with metastatic cancer can significantly impact decisions regarding treatment, care setting, and future planning. We evaluated the prognostication ability of a multidisciplinary team (MDT) experienced in providing supportive care and palliative radiotherapy.

Methods

After clinical assessment of consecutive patients, survival predictions were independently made by each MDT member. Patient demographics, factors influencing predictions, and dates of death were collected. Clinical predictions of survival (CPS) were considered correct if within 30 days of actual survival (AS). Summary statistics and Kaplan–Meier estimates of overall survival were obtained. Correlations between actual and CPS were calculated using Spearman's correlation coefficient. Multivariate logistic regression analysis identified factors associated with prognostication accuracy.

Results

A total of 395 predictions (06/2010–07/2012) were made by eight disciplines. Average age was 68 years, 68.3 % of patients were male, and 48.4 % had lung cancer. Median AS was 87 days (95 % CI 66–102 days). Survival was over-estimated 72.4 % (286/395) of the time with r = 0.54 (p < 0.0001) for all predictions across all disciplines. In addition, 30.3 % (36/119) of radiation therapist (RTT) predictions were correct compared to 30.1 % (22/73) of nurses', 28.7 % (43/150) of physicians', and 15.1 % (8/53) of allied health (AH) providers. There were no differences in accuracy by discipline except for the RTT versus AH groups (p = 0.04). Factors most frequently cited as influencing correct predictions were Karnofsky performance status (KPS), extent of disease, and histology. KPS was the only significant variable on multivariate analysis (p ≤ 0.04).

Conclusion

MDT members providing collaborative care for advanced cancer patients utilize similar factors in predicting survival with comparable accuracy.

Keywords

Cancer Survival prediction Multidisciplinary Radiotherapy Palliative 

Notes

Acknowledgments

We are grateful to all Palliative Radiation Oncology multidisciplinary team members at the Cross Cancer Institute for their participation. Presented in part at the Supportive Care in Cancer 25th International Symposium, June 28–30, 2012, New York City, NY; ASTRO 54th Annual Meeting, Oct 28-Nov 1, 2012, Boston, MA; and the CARO Annual Scientific Meeting, 12–15 Sept 2012, Ottawa, ON. Recognized by the Multinational Association for Supportive Care in Cancer with a Young Investigator Award (B Debenham; 2012).

Conflict of interest

There are no actual or potential conflicts of interest to declare. There is no funding source to acknowledge. The authors have full control of all primary data which can be reviewed by the journal if requested.

References

  1. 1.
    Glare P, Sinclair C, Downing M, Stone P, Maltoni M, Vigano A (2008) Predicting survival in patients with advanced disease. Eur J Cancer 44(8):1146–1156PubMedCrossRefGoogle Scholar
  2. 2.
    Gripp S, Moeller S, Bolke E et al (2007) Survival prediction in terminally ill cancer patients by clinical estimates, laboratory tests and self-rated anxiety and depression. J Clin Oncol 25(22):3313–3320PubMedCrossRefGoogle Scholar
  3. 3.
    Glare P (2005) Clinical predictors of survival in advanced cancer. J Support Oncol 3:331–339PubMedGoogle Scholar
  4. 4.
    Maltoni M, Caraceni A, Brunelli C et al (2005) Prognostic factors in advanced cancer patients: evidence-based clinical recommendations—a study by the steering committee of the European Association for Palliative Care. J Clin Oncol 23(25):6240–6248PubMedCrossRefGoogle Scholar
  5. 5.
    Addington-Hall J, MacDonald L, Anderson (1990) Can the Spitzer Quality of Life Index help to reduce prognostic uncertainty in terminal care? Br J Cancer 62:695–699PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Mackillop W, Quirt C (1997) Measuring the accuracy of prognostic judgments in oncology. J Clin Epidemiol 50(1):21–29PubMedCrossRefGoogle Scholar
  7. 7.
    Gwilliam B, Keeley V, Todd C et al (2011) Development of prognosis in palliative care study predictor models to improve prognostication in advanced cancer: prospective cohort study. BMJ 343:4920–4934CrossRefGoogle Scholar
  8. 8.
    Pearlman R (1988) Inaccurate predictions of life expectancy: dilemmas and opportunities. Arch Intern Med 148:2537–2538PubMedCrossRefGoogle Scholar
  9. 9.
    Gwilliam B, Keeley V, Todd C et al (2012) Prognosticating in patients with advanced cancer—observational study comparing the accuracy of clinicians' and patients' estimates of survival. Ann Oncol 1–7Google Scholar
  10. 10.
    Hagerty R, Butow P, Ellis P et al (2005) Communicating with realism and hope: incurable cancer patients' views on the disclosure of prognosis. J Clin Oncol 23:1278–1288PubMedCrossRefGoogle Scholar
  11. 11.
    Glare P, Virik K, Jones M et al (2003) A systematic review of physicians' survival predictions in terminally ill cancer patients. BMJ 327:195–198PubMedCrossRefGoogle Scholar
  12. 12.
    Bruera E, Miller M, Kuehn N, MacEachern T, Hanson J (1992) Estimate of survival of patients admitted to a palliative care unit: a prospective study. J Pain Sympt Manage 7:82–86CrossRefGoogle Scholar
  13. 13.
    Christakis N, Lamont E (2000) Extent and determinants of error in doctors' prognoses in terminally ill patients: prospective cohort study. BMJ 320:469–472PubMedCrossRefGoogle Scholar
  14. 14.
    Vigano A, Dorgan M, Bruera E, Suarez-Almazor M (1999) The relative accuracy of the clinical estimation of the duration of life for patients with end of life cancer. Cancer 86:170–176PubMedCrossRefGoogle Scholar
  15. 15.
    Heyse-Moore L, Johnson-Bell V (1987) Can doctors accurately predict the life expectancy of patients with terminal cancer? Pall Med 1:165–166CrossRefGoogle Scholar
  16. 16.
    Hui D, Kilgore K, Nguyen L et al (2011) The accuracy of probabilistic versus temporal clinician prediction of survival for patients with advanced cancer: a preliminary report. Oncologist 16:1642–1648PubMedCrossRefGoogle Scholar
  17. 17.
    Casarett D (2006) The median is not the (only) message. Ann Intern Med 145(9):700–701PubMedCrossRefGoogle Scholar
  18. 18.
    Buchan J (1995) Nurses' estimations of patients' prognoses in the last days of life. Int J Pall Nurs 1(1):12–16Google Scholar
  19. 19.
    Glare P (2006) Prognostic factors in terminal cancer. In: Gospodarowicz M (ed) Prognostic factors in cancer, 2nd edn. Wiley-Liss, HobokenGoogle Scholar
  20. 20.
    Hauser C, Stockler M, Tattersall M (2006) Prognostic factors in patients with recently diagnosed incurable cancer: a systematic review. Support Care Cancer 14(10):999–1011PubMedCrossRefGoogle Scholar
  21. 21.
    Vigano A, Donaldson N, Higginson I et al (2004) Quality of life and survival prediction in terminal cancer patients: a multicenter study. Cancer 101:1090–1098PubMedCrossRefGoogle Scholar
  22. 22.
    Twomey F, O'Leary N, O'Brien T (2008) Prediction of patient survival by healthcare professionals in a specialist palliative care inpatient unit: a prospective study. Am J Hosp Pall Med 25(2):139–145CrossRefGoogle Scholar
  23. 23.
    Phillips D, Smith D (1990) Postponement of death until symbolically meaningful occasions. JAMA 263:1947–1951PubMedCrossRefGoogle Scholar
  24. 24.
    Allison P, Guichard C, Fung K, Gilain L (2003) Dispositional optimism predicts survival status one year after diagnosis in head and neck cancer. J Clin Oncol 21:543–548PubMedCrossRefGoogle Scholar
  25. 25.
    Schoenbach V, Kaplan B, Fredman L, Kleinbaum D (1986) Social ties and mortality in Evans County, Georgia. Am J Epidemiol 123:577–591PubMedGoogle Scholar
  26. 26.
    Gagnon L, Fairchild A, Pituskin E, Dutka J, Chambers C (2012) Optimizing pain relief in a specialized outpatient palliative radiotherapy clinic: contributions of a clinical pharmacist. J Oncol Pharm Pract 18(1):70–77CrossRefGoogle Scholar
  27. 27.
    Danielson B, Fairchild A (2012) Beyond palliative radiotherapy: a pilot multidisciplinary brain metastases clinic. Support Care Cancer 20(4):773–781PubMedCrossRefGoogle Scholar
  28. 28.
    Pituskin E, Fairchild A, Driga A et al (2010) Multidisciplinary team contributions within a dedicated outpatient palliative radiotherapy clinic: a prospective descriptive study. Int J Rad Oncol Biol Phys 78(2):527–532CrossRefGoogle Scholar
  29. 29.
    Fairchild A, Pituskin E, Rose B et al (2009) The rapid access palliative radiotherapy program: blueprint for initiation of a one-stop multidisciplinary bone metastases clinic. Support Care Cancer 17(2):163–170PubMedCrossRefGoogle Scholar
  30. 30.
    Forster L, Lynn J (1988) Predicting life span for applicants to inpatient hospice. Arch Intern Med 148:2540–2543PubMedCrossRefGoogle Scholar
  31. 31.
    Bland M (2000) An introduction to medical statistics, 3rd edn. Oxford University Press, OxfordGoogle Scholar
  32. 32.
    Parkes C (1972) Accuracy of predictions of survival in later stages of cancer. BMJ 2:29–31PubMedCrossRefGoogle Scholar
  33. 33.
    Morita T, Tsunoda J, Inoue S, Chihara S (2001) Improved accuracy of physicians' survival prediction for terminally ill cancer patients using the Palliative Prognostic Index. Pall Med 15:419–424CrossRefGoogle Scholar
  34. 34.
    Kee F, Owen T, Leathem R (2007) Offering a prognosis in lung cancer: when is a team of experts an expert team? J Epidemiol Community Health 61:308–313PubMedCrossRefGoogle Scholar
  35. 35.
    Clarke M, Ewings P, Hanna T, Dunn L, Girling T, Widdison A (2009) How accurate are doctors, nurses and medical students at predicting life expectancy? Eur J Int Med 20:640–644CrossRefGoogle Scholar
  36. 36.
    Bruera E (2005) The clinical and research implications of survival prediction. J Sup Oncol 3:342–343Google Scholar
  37. 37.
    Oxenham D, Cornbleet M (1998) Accuracy of prediction of survival by different professional groups in a hospice. Pall Med 12:117–118CrossRefGoogle Scholar
  38. 38.
    Llobera J, Esteva M, Rifa J et al (2000) Terminal cancer: duration and prediction of survival time. Eur J Cancer 36:2036–2043PubMedCrossRefGoogle Scholar
  39. 39.
    Lamont E, Christakis C (2001) Prognostic disclosure to patients with cancer near the end of life. Ann Intern Med 134:1096–1105PubMedCrossRefGoogle Scholar
  40. 40.
    Christakis N, Iwashyna T (1998) Attitude and self-reported practice regarding prognostication in a national sample of internists. Arch Intern Med 158(21):2389–2395PubMedCrossRefGoogle Scholar
  41. 41.
    Chow E, Harth T, Hruby G, Finkelstein J, Wu J, Danjoux C (2001) How accurate are physicians' clinical predictions of survival and the available prognostic tools in estimating survival times in terminally ill cancer patients? A systematic review. Clin Oncol 13:209–218Google Scholar
  42. 42.
    Dawes R, Faust D, Meehl P (1989) Clinical versus actuarial judgement. Science 243:1668–1674PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • A Fairchild
    • 1
    Email author
  • B Debenham
    • 1
  • B Danielson
    • 1
  • F Huang
    • 1
  • S Ghosh
    • 2
  1. 1.Department of Radiation Oncology, Palliative Radiation Oncology ProgramCross Cancer InstituteEdmontonCanada
  2. 2.Department of Experimental OncologyCross Cancer InstituteEdmontonCanada

Personalised recommendations