Evidence map›Paper›PMID 37848745›Full record

ArticleInternational urology and nephrology2024

Development and internal validation of a nomogram predicting 3-year chronic kidney disease upstaging following robot-assisted partial nephrectomy.

Rocco Simone Flammia, Umberto Anceschi, Gabriele Tuderti, Fabrizio Di Maida, Antonio Andrea Grosso, Luca Lambertini, Andrea Mari, Riccardo Mastroianni, Alfredo Bove, Umberto Capitanio and 10 more

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Article in International urology and nephrology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
8.8field-weighted citation impact, top 2% 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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

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  9. Acute kidney injury in urological conditions.Asian biomedicine : research, reviews and news · 2026
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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

20 authors at 7 institutions in 3 countries.

Rocco Simone FlammiaDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy. roccosimone92@gmail.com.ORCID http://orcid.org/0000-0002-3129-0544
Umberto AnceschiDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Gabriele TudertiDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Fabrizio Di MaidaDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Antonio Andrea GrossoDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Luca LambertiniDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Andrea MariDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Riccardo MastroianniDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Alfredo BoveDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Umberto CapitanioDivision of Experimental Oncology, Urological Research Institute (URI), IRCCS Ospedale San Raffaele, Milan, Italy.
Daniele AmparoreDepartment of Urology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy.
Jennifer LeeDepartment of Urology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Savio D PandolfoDepartment of Urology, Rush University, Chicago, IL, USA.
Cristian FioriDepartment of Urology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy.
Andrea MinerviniDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Francesco PorpigliaDepartment of Urology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy.
Daniel EunDepartment of Urology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Riccardo AutorinoDepartment of Urology, Rush University, Chicago, IL, USA.
Costantino LeonardoDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Giuseppe SimoneDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Istituti di Ricovero e Cura a Carattere Scientifico · ITAzienda Ospedaliero-Universitaria Careggi · ITUniversity of Turin · ITRush University · USTemple University · USIRCCS Ospedale San Raffaele · ITNational Cancer Institute · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAim of the present study was to develop and validate a nomogram to accurately predict the risk of chronic kidney disease (CKD) upstaging at 3 years in patients undergoing robot-assisted partial nephrectomy (RAPN).

methodsA multi-institutional database was queried to identify patients treated with RAPN for localized renal tumor (cT1-cT2, cN0, cM0). Significant CKD upstaging (sCKD-upstaging) was defined as development of newly onset CKD stage 3a, 3b, and 4/5. Model accuracy was calculated according to Harrell C-index. Subsequently, internal validation using bootstrapping and calibration was performed. Then nomogram was depicted to graphically calculate the 3-year sCKD-upstaging risk. Finally, regression tree analysis identified potential cut-offs in nomogram-derived probability. Based on this cut-off, four risk classes were derived with Kaplan-Meier analysis tested this classification.

resultsOverall, 965 patients were identified. At Kaplan-Meier analysis, 3-year sCKD-upstaging rate was 21.4%. The model included baseline (estimated glomerular filtration rate) eGFR, solitary kidney status, multiple lesions, R.E.N.A.L. nephrometry score, clamping technique, and postoperative acute kidney injury (AKI). The model accurately predicted 3-year sCKD-upstaging (C-index 84%). Based on identified nomogram cut-offs (7 vs 16 vs 26%), a statistically significant increase in sCKD-upstaging rates between low vs intermediate favorable vs intermediate unfavorable vs high-risk patients (1.3 vs 9.2 vs 22 vs 54.2%, respectively, p < 0.001) was observed.

conclusionHerein we introduce a novel nomogram that can accurately predict the risk of sCKD-upstaging at 3 years. Based on this nomogram, it is possible to identify four risk categories. If externally validated, this nomogram may represent a useful tool to improve patient counseling and management.

Indexed as

Kidney NeoplasmsRenal Insufficiency, ChronicRoboticsRobotic Surgical ProceduresGlomerular Filtration RateHumansNephrectomyNomogramsRetrospective StudiesTreatment OutcomeChronic kidney failureNephrectomyNomogramRenal cancerRobot-assisted partial nephrectomy

Identifiers

PMID37848745
OpenAlexW4387696432

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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.