Featured Research

from universities, journals, and other organizations

More work needed on models to predict risk of chronic kidney disease

Date:
November 20, 2012
Source:
Public Library of Science
Summary:
Models used for predicting the likelihood of individuals developing chronic kidney disease and for predicting disease progression in people who already have the condition are useful tools but not yet robust enough to help inform clinical guidelines, according to a new study.

Models used for predicting the likelihood of individuals developing chronic kidney disease and for predicting disease progression in people who already have the condition are useful tools but not yet robust enough to help inform clinical guidelines, according to a study published in this week's PLOS Medicine.

Chronic kidney disease is a common but serious condition which can lead to kidney failure. The condition cannot be cured but progression of the disease can be slowed by controlling high blood pressure and diabetes, both causes of chronic kidney disease, and by adopting a healthy lifestyle. Identifying people who are at risk of developing chronic kidney disease is therefore of utmost importance and researchers are currently using "risk models" -- a method to assess the risk of developing the condition -- as currently, there is no screening test for chronic kidney disease.

Justin Echouffo-Tcheugui from Emory University in Atlanta, Georgia, and Andre Kengne from the South African Medical Research Council in Capetown reviewed published studies to test the accuracy and suitability of existing risk models for chronic kidney disease. They found that although the risk models were able to separate people with chronic kidney disease from those without the condition (discriminatory ability) not all of the models checked whether the proportion of the population predicted to develop chronic kidney disease (based on the average predictive risk calculated by the models) actually developed the condition (calibration).

The authors also found that few studies tested the risk model in other groups (other than the specific study group) and most of the models were only tested in Caucasian populations.

The authors say: "This review suggests that risk models for predicting chronic kidney disease or its progression have a modest-to-acceptable discriminatory performance, but would need to be better calibrated and externally validated -- and the impact of their use on outcomes assessed -- before these are incorporated in guidelines."

In an accompanying Perspective article, Maarten Taal (uninvolved in the study) from the Royal Derby Hospital in the UK stresses the importance of a potential screening test for chronic kidney disease but says: "Efforts to develop risk prediction tools to target screening towards those at higher risk are likely to improve the efficiency of screening programmes, but as noted by Echouffo-Tcheugui and Kegne, published risk prediction formulae require further development and external validation."

Taal continues: "In the absence of evidence showing benefit from population screening for chronic kidney disease most guidelines recommend that testing should be directed to people with known risk factors, but in light of improved diagnostic tests and novel risk prediction tools, further research is required to establish the most cost-effective approach."


Story Source:

The above story is based on materials provided by Public Library of Science. Note: Materials may be edited for content and length.


Journal Reference:

  1. Justin B. Echouffo-Tcheugui, Andre P. Kengne. Risk Models to Predict Chronic Kidney Disease and Its Progression: A Systematic Review. PLoS Medicine, 2012; 9 (11): e1001344 DOI: 10.1371/journal.pmed.1001344

Cite This Page:

Public Library of Science. "More work needed on models to predict risk of chronic kidney disease." ScienceDaily. ScienceDaily, 20 November 2012. <www.sciencedaily.com/releases/2012/11/121120194930.htm>.
Public Library of Science. (2012, November 20). More work needed on models to predict risk of chronic kidney disease. ScienceDaily. Retrieved July 30, 2014 from www.sciencedaily.com/releases/2012/11/121120194930.htm
Public Library of Science. "More work needed on models to predict risk of chronic kidney disease." ScienceDaily. www.sciencedaily.com/releases/2012/11/121120194930.htm (accessed July 30, 2014).

Share This




More Health & Medicine News

Wednesday, July 30, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Health Insurers' Profits Slide

Health Insurers' Profits Slide

Reuters - Business Video Online (July 30, 2014) Obamacare-related costs were said to be behind the profit plunge at Wellpoint and Humana, but Wellpoint sees the new exchanges boosting its earnings for the full year. Fred Katayama reports. Video provided by Reuters
Powered by NewsLook.com
Concern Grows Over Worsening Ebola Crisis

Concern Grows Over Worsening Ebola Crisis

AFP (July 30, 2014) Pan-African airline ASKY has suspended all flights to and from the capitals of Liberia and Sierra Leone amid the worsening Ebola health crisis, which has so far caused 672 deaths in Guinea, Liberia and Sierra Leone. Duration: 00:43 Video provided by AFP
Powered by NewsLook.com
At Least 20 Chikungunya Cases in New Jersey

At Least 20 Chikungunya Cases in New Jersey

AP (July 30, 2014) At least 20 New Jersey residents have tested positive for chikungunya, a mosquito-borne virus that has spread through the Caribbean. (July 30) Video provided by AP
Powered by NewsLook.com
Generics Eat Into Pfizer's Sales

Generics Eat Into Pfizer's Sales

Reuters - Business Video Online (July 29, 2014) Pfizer, the world's largest drug maker, cut full-year revenue forecasts because generics could cut into sales of its anti-arthritis drug, Celebrex. Fred Katayama reports. Video provided by Reuters
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

    Environment News

    Technology News



      Save/Print:
      Share:

      Free Subscriptions


      Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

      Get Social & Mobile


      Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

      Have Feedback?


      Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
      Mobile: iPhone Android Web
      Follow: Facebook Twitter Google+
      Subscribe: RSS Feeds Email Newsletters
      Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins