Evidence map›Paper›PMID 35842890›Full record

ArticleInternational urology and nephrology2022

Optimizing prediction of new-baseline glomerular filtration rate after radical nephrectomy: are algorithms really necessary?

Nityam Rathi, Yosuke Yasuda, Worapat Attawettayanon, Diego A Palacios, Yunlin Ye, Jianbo Li, Christopher Weight, Mohammed Eltemamy, Tarik Benidir, Robert Abouassaly and 1 more

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In one paragraph

Article in International urology and nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Management and optimization of chronic renal insufficiency in the setting of kidney cancer A Systematic Review.International braz j urol : official journal of the Brazilian Society of Urology
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 4 countries.

Nityam RathiCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Yosuke YasudaCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Worapat AttawettayanonCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Diego A PalaciosCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Yunlin YeCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Jianbo LiDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
Christopher WeightCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Mohammed EltemamyCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Tarik BenidirCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Robert AbouassalyCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Steven C CampbellCenter for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA. campbes3@ccf.org.
Cleveland Clinic · USPrince of Songkla University · THTokyo Medical and Dental University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRadical nephrectomy (RN) is an important consideration for the management of localized renal-cell-carcinoma (RCC) whenever the tumor appears aggressive, although reduced renal function is a concern. Split-renal-function (SRF) in the contralateral kidney and postoperative renal functional compensation (RFC) are fundamentally important for the accurate prediction of new baseline GFR (NBGFR) post-RN. SRF can be estimated either from nuclear renal scans (NRS) or from preoperative imaging using parenchymal-volume-analysis (PVA). We compare two SRF-based models for predicting NBGFR after RN with a subjective prediction of NBGFR by an experienced urologic-oncologist.

methods187 RCC patients managed with RN (2006-16) were included based on the availability of preoperative CT/MRI and NRS, and preoperative/postoperative eGFR. NBGFR was defined as the final GFR 3-12 months post-RN. For the SRF-based approaches, SRF was derived from either NRS or PVA, and RFC was estimated at 25% based on previous independent analyses. Thus, the formula (Global GFR

resultsThe r values for subjective-assessment, NRS/SRF-based, and PVA/SRF-based approaches were 0.72/0.72/0.85, respectively (p < 0.05). The PVA/SRF-based model also demonstrated significant improvement across other performance parameters.

conclusionsThe PVA/SRF-based model more accurately predicts NBGFR post-RN than NRS/SRF-based and Subjective Estimation. PVA software (Fujifilm-medical-systems) is readily available and affordable and provides accurate SRF estimations from routine preoperative imaging. This novel approach may inform clinical management regarding RN/PN for complex RCC cases.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsAlgorithmsGlomerular Filtration RateHumansKidneyNephrectomyRetrospective StudiesFunctional compensationKidney cancerParenchymal volume analysisRadical nephrectomySplit renal function

Identifiers

PMID35842890
OpenAlexW4285676677

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.