ASN's Mission

ASN leads the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005


The Latest on Twitter

Kidney Week

Abstract: FR-PO908

External Validation of a Short-Term Prognostic Model for Patients Who Are on Maintenance Hemodialysis

Session Information

Category: Dialysis

  • 609 Dialysis: Palliative and End-of-Life Care


  • Kittanamongkolchai, Wonngarm, Mayo Clinic, Rochester, Minnesota, United States
  • Gonzalez Suarez, M. Lourdes, Mayo Clinic, Rochester, Minnesota, United States
  • Gregoire, James Robert, Mayo Clinic, Rochester, Minnesota, United States

Simple and accurate instruments for prognostication are needed to enable nephrologists to identify dialysis patients who have a poor prognosis and benefit from palliative care and advance care planning. Prognostic models have been developed but external validation studies are scarce. We aimed to externally validate a short-term prognostic model among our dialysis patients.


Between October 1 to October 31 2015, all of the adult HD patients (n =89) at a single dialysis facility in Rochester, MN were screened. Patient charts were reviewed for actuarial predictors (age, serum albumin, dementia and peripheral vascular disease) and nephrologists answered the “surprise” question, “Would I be surprised if this patient died within the next 6 months?”. One-year survival was calculated using the prognostic calculator tool derived from a study by Cohen et al1( H:\QI palliative\Prospective study\Prognosis calculator.htm ) with each patient’s individual covariates. Survival was monitored for 12 months. We assessed the predictive accuracy of the short-term prognostic model by calculating c-index based on the receiver operating characteristic curve.


The mean predicted 1-year mortality was 19% compared with the observed mortality of 12%. The model had a C-index of 0.82 (p = 0.0001). Thirty eight percent of patients with 1-y predicted survival rate in the lowest quartile (equal or less than 66%) died compared to 3% of those with 1-Y predicted survival rate more than 66%. As seen in Figure 1, the model successfully predicted which patients had worse and better survival over time.


The short-term prognostic tool for dialysis patients may be of value for clinicians to improve end-of-life care by providing more accurate prognostic information.

1. Cohen LM, et al. Clin J Am Soc Nephrol. 2010 Jan;5(1):72-9

Figure 1: Survival of patients with predicted 1-Y survival in the lowest quartile (blue line) and higher quartiles (red line)