Literature DB >> 24855282

Developing risk prediction models for kidney injury and assessing incremental value for novel biomarkers.

Kathleen F Kerr1, Allison Meisner1, Heather Thiessen-Philbrook2, Steven G Coca3, Chirag R Parikh4.   

Abstract

The field of nephrology is actively involved in developing biomarkers and improving models for predicting patients' risks of AKI and CKD and their outcomes. However, some important aspects of evaluating biomarkers and risk models are not widely appreciated, and statistical methods are still evolving. This review describes some of the most important statistical concepts for this area of research and identifies common pitfalls. Particular attention is paid to metrics proposed within the last 5 years for quantifying the incremental predictive value of a new biomarker.
Copyright © 2014 by the American Society of Nephrology.

Entities:  

Keywords:  AUC; biomarkers; kidney injury; net reclassification improvement; risk prediction

Mesh：

Substances：

Year:  2014        PMID： 24855282      PMCID： PMC4123400          DOI： 10.2215/CJN.10351013

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN： 1555-9041            Impact factor:   8.237


  35 in total

1.  New metrics for assessing diagnostic potential of candidate biomarkers.

Authors:  John W Pickering; Zoltan H Endre
Journal:  Clin J Am Soc Nephrol       Date:  2012-06-07       Impact factor: 8.237

2.  Biomarkers predict progression of acute kidney injury after cardiac surgery.

Authors:  Jay L Koyner; Amit X Garg; Steven G Coca; Kyaw Sint; Heather Thiessen-Philbrook; Uptal D Patel; Michael G Shlipak; Chirag R Parikh
Journal:  J Am Soc Nephrol       Date:  2012-03-01       Impact factor: 10.121

3.  Testing for improvement in prediction model performance.

Authors:  Margaret Sullivan Pepe; Kathleen F Kerr; Gary Longton; Zheyu Wang
Journal:  Stat Med       Date:  2013-01-07       Impact factor: 2.373

4.  Automated variable selection methods for logistic regression produced unstable models for predicting acute myocardial infarction mortality.

Authors:  Peter C Austin; Jack V Tu
Journal:  J Clin Epidemiol       Date:  2004-11       Impact factor: 6.437

5.  Use and misuse of the receiver operating characteristic curve in risk prediction.

Authors:  Nancy R Cook
Journal:  Circulation       Date:  2007-02-20       Impact factor: 29.690

6.  A unified inference procedure for a class of measures to assess improvement in risk prediction systems with survival data.

Authors:  Hajime Uno; Lu Tian; Tianxi Cai; Isaac S Kohane; L J Wei
Journal:  Stat Med       Date:  2012-10-05       Impact factor: 2.373

7.  Categorisation of continuous exposure variables revisited. A response to the Hyperglycaemia and Adverse Pregnancy Outcome (HAPO) Study.

Authors:  Kathrine F Frøslie; Jo Røislien; Petter Laake; Tore Henriksen; Elisabeth Qvigstad; Marit B Veierød
Journal:  BMC Med Res Methodol       Date:  2010-11-09       Impact factor: 4.615

Review 8.  Urinary and serum biomarkers for the diagnosis of acute kidney injury: an in-depth review of the literature.

Authors:  Jill Vanmassenhove; Raymond Vanholder; Evi Nagler; Wim Van Biesen
Journal:  Nephrol Dial Transplant       Date:  2012-10-31       Impact factor: 5.992

Review 9.  Net reclassification indices for evaluating risk prediction instruments: a critical review.

Authors:  Kathleen F Kerr; Zheyu Wang; Holly Janes; Robyn L McClelland; Bruce M Psaty; Margaret S Pepe
Journal:  Epidemiology       Date:  2014-01       Impact factor: 4.822

10.  Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury.

Authors:  Ravindra L Mehta; John A Kellum; Sudhir V Shah; Bruce A Molitoris; Claudio Ronco; David G Warnock; Adeera Levin
Journal:  Crit Care       Date:  2007       Impact factor: 9.097
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  18 in total

Review 1.  What can we expect from biomarkers for acute kidney injury?

Authors:  John A Kellum; Prasad Devarajan
Journal:  Biomark Med       Date:  2014       Impact factor: 2.851

2.  Evaluating biomarkers for prognostic enrichment of clinical trials.

Authors:  Kathleen F Kerr; Jeremy Roth; Kehao Zhu; Heather Thiessen-Philbrook; Allison Meisner; Francis Perry Wilson; Steven Coca; Chirag R Parikh
Journal:  Clin Trials       Date:  2017-08-10       Impact factor: 2.486

3.  Association of Renal Stress/Damage and Filtration Biomarkers with Subsequent AKI during Hospitalization among Patients Presenting to the Emergency Department.

Authors:  Martin Kimmel; Jing Shi; Joerg Latus; Christoph Wasser; Daniel Kitterer; Niko Braun; Mark Dominik Alscher
Journal:  Clin J Am Soc Nephrol       Date:  2016-03-29       Impact factor: 8.237

4.  Utility of Biomarkers to Improve Prediction of Readmission or Mortality After Cardiac Surgery.

Authors:  Jeremiah R Brown; Jeffrey P Jacobs; Shama S Alam; Heather Thiessen-Philbrook; Allen Everett; Donald S Likosky; Kevin Lobdell; Moritz C Wyler von Ballmoos; Devin M Parker; Amit X Garg; Todd Mackenzie; Marshall L Jacobs; Chirag R Parikh
Journal:  Ann Thorac Surg       Date:  2018-08-04       Impact factor: 4.330

Review 5.  Methodological issues in current practice may lead to bias in the development of biomarker combinations for predicting acute kidney injury.

Authors:  Allison Meisner; Kathleen F Kerr; Heather Thiessen-Philbrook; Steven G Coca; Chirag R Parikh
Journal:  Kidney Int       Date:  2016-02       Impact factor: 10.612

6.  Uromodulin to Osteopontin Ratio in Deceased Donor Urine Is Associated With Kidney Graft Outcomes.

Authors:  Sherry G Mansour; Caroline Liu; Yaqi Jia; Peter P Reese; Isaac E Hall; Tarek M El-Achkar; Kaice A LaFavers; Wassim Obeid; Avi Z Rosenberg; Parnaz Daneshpajouhnejad; Mona D Doshi; Enver Akalin; Jonathan S Bromberg; Meera N Harhay; Sumit Mohan; Thangamani Muthukumar; Bernd Schröppel; Pooja Singh; Joe M El-Khoury; Francis L Weng; Heather R Thiessen-Philbrook; Chirag R Parikh
Journal:  Transplantation       Date:  2021-04-01       Impact factor: 4.939

Review 7.  Statistical Methods for Cohort Studies of CKD: Prediction Modeling.

Authors:  Jason Roy; Haochang Shou; Dawei Xie; Jesse Y Hsu; Wei Yang; Amanda H Anderson; J Richard Landis; Christopher Jepson; Jiang He; Kathleen D Liu; Chi-Yuan Hsu; Harold I Feldman
Journal:  Clin J Am Soc Nephrol       Date:  2016-09-22       Impact factor: 10.614

8.  Accounting for established predictors with the multistep elastic net.

Authors:  Elizabeth C Chase; Philip S Boonstra
Journal:  Stat Med       Date:  2019-07-17       Impact factor: 2.373

9.  RiGoR: reporting guidelines to address common sources of bias in risk model development.

Authors:  Kathleen F Kerr; Allison Meisner; Heather Thiessen-Philbrook; Steven G Coca; Chirag R Parikh
Journal:  Biomark Res       Date:  2015-01-24

10.  Value of adding the renal pathological score to the kidney failure risk equation in advanced diabetic nephropathy.

Authors:  Masayuki Yamanouchi; Junichi Hoshino; Yoshifumi Ubara; Kenmei Takaichi; Keiichi Kinowaki; Takeshi Fujii; Kenichi Ohashi; Koki Mise; Tadashi Toyama; Akinori Hara; Kiyoki Kitagawa; Miho Shimizu; Kengo Furuichi; Takashi Wada
Journal:  PLoS One       Date:  2018-01-16       Impact factor: 3.240
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