Hostname: page-component-77c89778f8-vsgnj Total loading time: 0 Render date: 2024-07-19T06:18:00.645Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessment of the impact of comorbidity on the survival of cancer patients treated by palliative care teams

Published online by Cambridge University Press:  03 September 2014

Claudio Calvo-Espinos ,
Estefania Ruiz De Gaona-Lana ,
Cristina Gonzalez-Anguren  and
Marcos Lama-Gay
Claudio Calvo-Espinos*
Affiliation:
Palliative Care Service, Hospital San Juan de Dios Pamplona, Navarra, Spain
Estefania Ruiz De Gaona-Lana
Affiliation:
Department of Hematology and Hemotherapy, Fundacion Hospital Calahorra, La Rioja, Spain
Cristina Gonzalez-Anguren
Affiliation:
Palliative Care Service, Hospital San Juan de Dios Pamplona, Navarra, Spain Primary Care Service, Peralta Primary Health Center, Oakland, California; Primary Care Service, Peralta Primary Health Center, Navarra, Spain
Marcos Lama-Gay
Affiliation:
Palliative Care Service, Hospital San Juan de Dios Pamplona, Navarra, Spain
*
Address correspondence and reprint requests to: Claudio Calvo, Palliative Care Service, Hospital San Juan de Dios Pamplona, Beloso Alto, 3 Planta Baja, 31006 Pamplona, Navarra, Spain. E-mail: clacales75@yahoo.es
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

The usefulness of the age-adjusted Charlson Comorbidity Index (ACCI) as a gauge of the impact of comorbidity on survival is known in the geriatric population. In palliative care, there is little research studying the correlation between comorbidity and survival in the advanced stages of oncological disease. The aim of our study was to explore the impact of comorbidity, measured with the ACCI, on survival in our patients. Our hypothesis was that higher ACCI scores would be associated with lower survival rates after the first visit.

Method:

We conducted a prospective observational study over one year. Patients were attended by palliative home care teams. The main variables were: survival from metastatic disease after the first visit and ACCI score on the first visit. We also employed a descriptive analysis and a Kaplan–Meier survival analysis, including different ranges of ACCI scores.

Results:

The final sample included 66 subjects. The standard patient was a 76-year-old man with lung cancer who had received chemotherapy. The overall average ACCI score was 10.45. Significant differences were found between the different locations of metastatic disease (greater survivals in breast, ovary, and prostate; p = 0.005) and some treatments (hormone and radiotherapy; p = 0.001 for each), but not from the first visit. We found lower survival rates among lung cancer patients with higher comorbidity (ACCI ≥ 11, p = 0.047), with no differences on other primary locations or overall values.

Significance of results:

The data show that comorbidity measured by the ACCI may be an interesting prognostic factor during the late stages of disease, as we have found in lung cancer. More research is certainly needed.

Keywords

ComorbiditySurvival analysisPrognosisAdvanced cancerPalliative care
Type
Original Articles
Information
Palliative & Supportive Care , Volume 13 , Issue 4 , August 2015 , pp. 1049 - 1055
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Albertsen, P.C., Moore, D.F., Shih, W., et al. (2011). Impact of comorbidity on survival among men with localized prostate cancer. Journal of Clinical Oncology, 29(10), 1335–1341.CrossRefGoogle ScholarPubMed
Alonso-Babarro, A., Bruera, E., Varela-Cerdeira, M., et al. (2011). Can this patient be discharged home? Factors associated with at-home death among patients with cancer. Journal of Clinical Oncology, 29(9), 1159–1167.Google Scholar
Beddhu, S., Bruns, S., Saul, M., et al. (2000). A simple comorbidity scale predicts clinical outcomes and costs in dialysis patients. The American Journal of Medicine, 108, 609–613.CrossRefGoogle ScholarPubMed
Birim, O., Kappetein, A.P. & Bogers, A.J. (2005). Charlson comorbidity index as a predictor of long-term outcome after surgery for non-small-cell lung cancer. European Journal of Cardio-Thoracic Surgery, 28, 759–762.Google Scholar
Blinderman, C.D., Homel, P., Billings, J.A., et al. (2009). Symptom distress and quality of life in patients with advanced chronic obstructive pulmonary disease. Journal of Pain and Symptom Management, 38(1), 115–123.Google Scholar
Charlson, M.E., Pompei, P., Ales, K.L., et al. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases, 40, 373–383.Google Scholar
Currow, D.C., Plummer, J., Frith, P., et al. (2007). Can we predict which patients with refractory dyspnea will respond to opioids? Journal of Palliative Medicine, 10(5), 1031–1036.Google Scholar
Fernández-Ruiz, M., Guerra-Vales, J.M. & Colina-Ruiz Delgado, F. (2009). Comorbidity negatively influences prognosis in patients with extrahepatic cholangiocarcinoma. World Journal of Gastroenterology, 15(42), 5279–5286.Google Scholar
Gettman, M.T., Boelter, C.W., Cheville, J.C., et al. (2003). Charlson Comorbidity Index as a predictor of outcome after surgery for renal cell carcinoma with renal vein, vena cava or right atrium extension. The Journal of Urology, 169, 1282.Google Scholar
Gomez-Baptiste, X., Viladiu, P., Fontanals, M.D., et al. (2001). Dying of cancer in Catalonia: A population-based study about the last month in the life of cancer patients (1993–94). Medicina Paliativa, 8(3), 134–137.Google Scholar
Guralnick, M.J. (1996). Assessing the impact of comorbidity in the older population. Annals of Epidemiology, 6, 376–380.Google Scholar
Gutiérrez-Misis, A., Sanchez-Santos, M. & Otero, A. (2012). Use of a proxy to the Charlson index to study the short- and long-term comorbidity and mortality in the elderly. Atención Primaria, 44(3), 153–161.Google Scholar
Hauser, C.A., Stockler, M.R. & Tatersall, M.H.N. (2006). Prognostic factors in patients with recently diagnosed incurable cancer: A systematic review. Supportive Care in Cancer, 14, 999–1011.CrossRefGoogle ScholarPubMed
Koppie, T.M., Serio, A.M., Vickers, A.J., et al. (2008). Age-adjusted Charlson comorbidity score is associated with treatment decisions and clinical outcomes for patients undergoing radical cystectomy for bladder cancer. Cancer, 112, 2384–2392.Google Scholar
Legler, A., Bradley, E. & Carlson, M.. (2011). The effect of comorbidity burden on healthcare utilization for patients with cancer using hospice. Journal of Palliative Medicine, 14(6), 751–756.CrossRefGoogle Scholar
Molina, J.M., Romero, Y., Romero, J., et al. (2008). Features of palliative cancer patients included in a palliative care programme. Medicina Paliativa, 15(2), 89–92.Google Scholar
Morita, T., Tsunoda, J., Inoue, S., et al. (1999). The Palliative Prognostic Index: A scoring system for survival prediction of terminally ill cancer patients. Supportive Care in Cancer, 7, 128–133.CrossRefGoogle ScholarPubMed
Navarre Health System (2008). Navarra cancer registry. Navarre, Spain: NHS.Google Scholar
Navarre Institute of Public Health (2007). Mortality in Navarre, 1997–2005. Journal of the Navarre Institute of Public Health, 44, 4.Google Scholar
Ouellette, J.R., Small, D.G. & Termuhlen, P.M. (2004). Evaluation of the Charlson Age Comorbidity Index as predictor of morbidity and mortality in patients with colorectal carcinoma. Journal of Gastrointestinal Surgery, 8, 1061–1067.Google Scholar
Piccirillo, J.F., Tierney, R.M., Costas, I., et al. (2004). Prognostic importance of comorbidity in a hospital-based cancer registry. The Journal of the American Medical Association, 291, 2441–2447.CrossRefGoogle Scholar
Pita, A.J., Cano, J.M. & Murillo, C. (2009). Aid profile of patients admitted to a medium- to long-term palliative care setting: A five-year experience. Medicina Paliativa, 16(6), 334–338.Google Scholar
Read, W.L., Tierney, R.M., Page, N.C., et al. (2004). Differential prognostic impact of comorbidity. Journal of Clinical Oncology, 22(15), 3099–3103.Google Scholar
Santos-Arrontes, D., Fernández Aceñero, M.J., García González, J.I., et al. (2008). Survival analysis of clear cell renal carcinoma according to the Charlson Comorbidity Index. The Journal of Urology, 179, 857–861.Google Scholar
Singh, B., Bhaya, M., Stern, J., et al. (1997). Validation of the Charlson Comorbidity Index in patients with head and neck cancer: A multi-institutional study. The Laryngoscope, 107, 1469–1475.CrossRefGoogle ScholarPubMed
Smith, S.L., Palma, D., Parhar, T., et al. (2011). Inoperable early stage non-small-cell lung cancer: Comorbidity, patterns of care and survival. Lung Cancer, 72(1), 39–44.Google Scholar
Temel, J.S., Greer, J.A., Muzikansky, A., et al. (2010). Early palliative care for patients with metastatic non-small-cell lung cancer. The New England Journal of Medicine, 363(8), 733–742.CrossRefGoogle ScholarPubMed
Tetsche, M.S., Dethlefsen, C., Pedersen, L., et al. (2008). The impact of comorbidity and stage on ovarian cancer mortality: A nationwide Danish cohort study. BMC Cancer, 8, 31.Google Scholar
Trujillo, R., Morgado, N., Pozo, R., et al. (2007). Assistance experience of the Palliative Care Program of the CUDECA Foundation. Medicina Paliativa, 14(4), 217–221.Google Scholar
Viguria, J. & Rocafort, J. (1999). Palliative care in Navarre Hospital, San Juan de Dios, Pamplona. Medicina Paliativa, 6(1), 33–38.Google Scholar
Yong, D.S., Kwok, A.O., Wong, D.M., et al. (2009). Symptom burden and quality of life in end-stage renal disease: A study of 179 patients on dialysis and palliative care. Palliative Medicine, 23, 111–119.Google Scholar