Effect of glomerular filtration rate at dialysis initiation on survival in patients with advanced chronic kidney disease: what is the effect of lead-time bias?

Abstract

Purpose

Current clinical guidelines recommend to initiate dialysis in the presence of symptoms or signs attributable to kidney failure, often with a glomerular filtration rate (GFR) of 5–10 mL/min/1.73 m². Little evidence exists about the optimal kidney function to start dialysis. Thus far, most observational studies have been limited by lead-time bias. Only a few studies have accounted for lead-time bias, and showed contradictory results. We examined the effect of GFR at dialysis initiation on survival in chronic kidney disease patients, and the role of lead-time bias therein. We used both kidney function based on 24-hour urine collection (measured GFR [mGFR]) and estimated GFR (eGFR).

Materials and methods

A total of 1,143 patients with eGFR data at dialysis initiation and 852 patients with mGFR data were included from the NECOSAD cohort. Cox regression was used to adjust for potential confounders. To examine the effect of lead-time bias, survival was counted from the time of dialysis initiation or from a common starting point (GFR 20 mL/min/1.73 m²), using linear interpolation models.

Results

Without lead-time correction, no difference between early and late starters was present based on eGFR (hazard ratio [HR] 1.03, 95% confidence interval [CI] 0.81–1.3). However, after lead-time correction, early initiation showed a survival disadvantage (HR between 1.1 [95% CI 0.82–1.48] and 1.33 [95% CI 1.05–1.68]). Based on mGFR, the potential survival benefit for early starters without lead-time correction (HR 0.8, 95% CI 0.62–1.03) completely disappeared after lead-time correction (HR between 0.94 [95% CI 0.65–1.34] and 1.21 [95% CI 0.95–1.56]). Dialysis start time differed about a year between early and late initiation.

Conclusion

Lead-time bias is not only a methodological problem but also has clinical impact when assessing the optimal kidney function to start dialysis. Therefore, lead-time bias is extremely important to correct for. Taking account of lead-time bias, this controlled study showed that early dialysis initiation (eGFR >7.9, mGFR >6.6 mL/min/1.73 m²) was not associated with an improvement in survival. Based on kidney function, this study suggests that in some patients, dialysis could be started even later than an eGFR <5.7 and mGFR <4.3 mL/min/1.73 m².

Keywords:

• end-stage renal disease
• epidemiology
• hazard model
• kidney function
• lead time
• linear interpolation model

Supplementary material

Hospitals participating in the NECOSAD study

Maasstad Hospital Rotterdam, Deventer Hospital Deventer, Sint Lucas Andreas Hospital Amsterdam, Academic Medical Center Amsterdam, Maxima Medical Center Veldhoven, Catharina Hospital Eindhoven, Medical Center Haaglanden Den Haag, University Medical Center Groningen, Kennemer Gasthuis Haarlem, Atrium Medical Center Heerlen, Medical Center Leeuwarden, Leiden University Medical Center Leiden, Elisabeth Hospital Tilburg, University Medical Center Utrecht, Antonius Ziekenhuis Nieuwegein, Hospital Gelderse Vallei Ede, Haga Hospital Leyenburg Den Haag, Academic Hospital Maastricht, Jeroen Bosch Hospital Den Bosch, Medisch Spectrum Twente Enschede, Albert Schweitzer Hospital Dordrecht, Alysis Zorggroep Rijnstate Hospital Arnhem, Dianet Dialysis Center Lunetten Utrecht, Canisius Wilhelmina Hospital Nijmegen, Vie Curi Medical Center Venlo, Leveste Scheper Hospital Emmen, Dianet Dialysis Center Holendrecht Amsterdam, Haga Hospital Rode Kruis Den Haag, Rijnland Hospital Leiderdorp, Admiraal de Ruyter ziekenhuis Goes, Medical Center Alkmaar, Laurentius Ziekenhuis Roermond, Dialysis Center ‘t Gooi Hilversum, Groene Hart Hospital Gouda, Westfries Gasthuis Hoorn, TergooiHospitals Hilversum, Martini Ziekenhuis Groningen, Zaans Medical Center Zaandam.

Formulae

To calculate estimated glomerular filtration rate (eGFR), we used the Modification of Diet in Renal Disease formula: $\begin{array}{l}\text{eGFR}\left(\text{mL}/\text{min}/1.73{\mathrm{m}}^2\right)=186\times \text{plasma}\\ \text{creatinine}/{88.4}^{-1.154}\times {\text{age}}^{-0.203}\times 0.742\left(\text{if female}\right)\times \\ 1.212\left(\text{if African}\right)\end{array}$(1)

To calculate measured GFR (mGFR) based on 24-hour urine samples, we used: $\begin{array}{l}\text{mGFR urea}=\text{urine urea}\left(\text{mmol}/\text{day}\right)/\text{plasma urea}\left(\text{mmol}/\mathrm{L}\right)\times \left(1,000/1,440\right)\\ \text{mGFR creatinine}=\text{urine creatinine}\left(\text{mmol}/\text{day}\right)/\left(\text{plasma creatinine}\left[\text{μmol}/\mathrm{L}\right]/1,000\right)\times \left(1,000/1,440\right)\\ \text{mGFR urea and creatinine}=\left(\text{mGFR urea}+\text{mGFR creatinine}\right)/2\\ \text{mGFR}\left(\text{mL}/\min /1.73{\mathrm{m}}^2\right)=\left(\text{mGFR urea and creatinine}\times 1.73\right)\times 10,000/({\text{weight}}^{0.424}\left[\text{kg}\right]\times {\text{height}}^{0.725}\left[\text{cm}\right]\times 71.84)\end{array}$(2)

PREPARE-1

PREPARE-1^1–3 was a retrospective follow-up study of 500 consecutive incident predialysis patients with chronic kidney disease stages 4–5. These patients were treated in one of the outpatient clinics of eight Dutch hospitals between 1999 and 2001. Patients had been referred to these outpatient clinics when creatinine clearance was below 20 mL/min. In addition, these patients were at least 18 years of age, had not had prior renal replacement therapy, and need for renal replacement therapy was expected within 1 year. The clinical course of predialysis patients was followed through medical charts until the start of dialysis, transplantation, death, loss to follow-up, or January 1, 2008, whichever came first.

Table S1 Annual rates of kidney function decline prior to dialysis initiation for late, intermediate, and early starters with available data in PREPARE-1 and NECOSAD

Table S2 Effect of GFR at dialysis initiation on survival and length of lead time

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Acknowledgments

The nursing staff of the 38 different dialysis units, who collected most of the data, are gratefully acknowledged for their assistance. Moreover, we thank the staff of the NECOSAD trial office for assistance in the logistics of this study. NECOSAD study group: EW Boeschoten, RT Krediet, AJ Apperloo, JA Bijlsma, M Boekhout, WH Boer, PJM van der Boog, HR Büller, M van Buren, FT de Charro, CJ Doorenbos, MA van den Dorpel, A van Es, WJ Fagel, GW Feith, CWH de Fijter, LAM Frenken, JACA van Geelen, PGG Gerlag, W Grave, JPMC Gorgels, RM Huisman, KJ Jager, K Jie, WAH Koning-Mulder, MI Koolen, TK Kremer Hovinga, ATJ Lavrijssen, AJ Luik, J van der Meulen, KJ Parlevliet, MHM Raasveld, FM van der Sande, MJM Schonck, MMJ Schuurmans, CEH Siegert, CA Stegeman, P Stevens, JGP Thijssen, RM Valentijn, G H Vastenburg, CA Verburgh, HH Vincent, PF Vos.

Disclosure

The authors report no conflicts of interest in this work.