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| Title |
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?
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|---|---|
| Published in |
Clinical Epidemiology, April 2017
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| DOI | 10.2147/clep.s127695 |
| Pubmed ID | |
| Authors |
Cynthia J Janmaat, Merel van Diepen, Raymond T Krediet, Marc H Hemmelder, Friedo W Dekker |
| Abstract |
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 m(2). 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). 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 m(2)), using linear interpolation models. 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. 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 m(2)) 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 m(2). |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 40% |
| Australia | 1 | 20% |
| United Kingdom | 1 | 20% |
| Curaçao | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 13% |
| Student > Doctoral Student | 2 | 7% |
| Student > Postgraduate | 2 | 7% |
| Librarian | 1 | 3% |
| Student > Ph. D. Student | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 17 | 57% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 5 | 17% |
| Medicine and Dentistry | 4 | 13% |
| Psychology | 2 | 7% |
| Mathematics | 1 | 3% |
| Unspecified | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 16 | 53% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 May 2020.
All research outputs
#14,602,413
of 25,703,943 outputs
Outputs from Clinical Epidemiology
#379
of 801 outputs
Outputs of similar age
#158,396
of 324,866 outputs
Outputs of similar age from Clinical Epidemiology
#12
of 15 outputs
Altmetric has tracked 25,703,943 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 801 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has gotten more attention than average, scoring higher than 51% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 324,866 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.