Literature DB >> 7043052

Analysis of survival of end-stage renal disease patients.

J M Weller, F K Port, R D Swartz, C W Ferguson, G W Williams, J F Jacobs.   

Abstract

Traditional life-table analysis of differences in patient survival for various end-stage renal disease (ESRD) treatment modalities ignore the fact the ESRD patients face sequential risks because they frequently experience more than one mode of therapy. A modification of the usual life-table analysis is suggested as being more appropriate. This modified method takes into account the "time-to-treatment" bias, which, in this instance, is the time spent on the first modality of treatment (that is, center dialysis). The survival data of more than 2,000 ESRD patients in the State of Michigan during the 5-year period, 1974 to 1978, are used to illustrate this method.

Entities:  

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Year:  1982        PMID: 7043052     DOI: 10.1038/ki.1982.11

Source DB:  PubMed          Journal:  Kidney Int        ISSN: 0085-2538            Impact factor:   10.612


  6 in total

1.  Occupational and other exposures associated with male end-stage renal disease: a case/control study.

Authors:  N K Steenland; M J Thun; C W Ferguson; F K Port
Journal:  Am J Public Health       Date:  1990-02       Impact factor: 9.308

2.  Effect of primary renal disease and risk factors on kidney graft survival.

Authors:  F Keller; J Hasselmann; G Offermann; W Hantelmann; M Molzahn; A Rost; M Maiga
Journal:  Int Urol Nephrol       Date:  1983       Impact factor: 2.370

3.  Social and contextual factors in the analysis of mortality in end-stage renal disease patients: implications for health policy.

Authors:  A L Plough; S Salem
Journal:  Am J Public Health       Date:  1982-11       Impact factor: 9.308

4.  Outcomes on home haemodialysis: registry challenges.

Authors:  Mark S MacGregor
Journal:  NDT Plus       Date:  2011-12

5.  Survival on home dialysis in New Zealand.

Authors:  Mark R Marshall; Rachael C Walker; Kevan R Polkinghorne; Kelvin L Lynn
Journal:  PLoS One       Date:  2014-05-07       Impact factor: 3.240

6.  Prediction of Mortality in Incident Hemodialysis Patients: A Validation and Comparison of CHADS2, CHA2DS2, and CCI Scores.

Authors:  Hsun Yang; Yi-Hsin Chen; Teng-Fu Hsieh; Shiun-Yang Chuang; Ming-Ju Wu
Journal:  PLoS One       Date:  2016-05-05       Impact factor: 3.240

  6 in total

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